Development and NMR validation of minimal pharmacophore hypotheses for the generation of fragment libraries enriched in heparanase inhibitors Rafael Gozalbes Æ Silvia Mosule ´n Æ Rodrigo J. Carbajo Æ Antonio Pineda-Lucena Received: 15 January 2009 / Accepted: 9 April 2009 / Published online: 7 May 2009 Ó Springer Science+Business Media B.V. 2009 Abstract A combined strategy based on the development of pharmacophore hypotheses and NMR approaches is reported for the identification of novel inhibitors of hepa- ranase, a key enzyme involved in tumor metastasis through the remodeling of the subepithelial and subendothelial basement membranes, resulting in the dissemination of metastatic cancer cells. Several pharmacophore hypotheses were initially developed from the most active heparanase inhibitors known to date and, after their application to a pool of 27 known heparanase inhibitors and a database of 1,120 compounds approved by the FDA, a four-point pharmacophore model was selected as the most predictive. This model was subsequently applied to a database of 686 chemical fragments, and a subset of 100 fragments accomplishing completely or partially the four-point model was selected to perform nuclear magnetic resonance experiments to validate the hypothesis. The experimental studies confirmed the reliability of our pharmacophore model, its applicability to in silico databases in order to reduce the number of compounds to be experimentally screened, and the possibility of generating fragment libraries enriched in heparanase inhibitors. Keywords Pharmacophore Á Fragment-based screening Á NMR Á Heparanase Á Inhibitor Introduction Heparanase is an endoglycosidase that acts at the cell- surface and within the extracellular matrix to degrade polymeric heparan sulfate molecules (Fig. 1) into shorter oligosaccharides [1, 2]. Heparanase is involved in several physiological activities such as embryo development, hair growth and wound healing, and it is also implicated in cancer processes such as tumor angiogenesis and metas- tasis [3, 4]. Increased levels of heparanase have been found in numerous cancer processes at different organs and there is a direct correlation between the overexpression of hep- aranase and the invasiveness of tumor cells [5]. The implication of heparanase in cancer progression makes it a very attractive target for anti-angiogenic, anti-metastatic and/or anti-inflammatory therapies. The three-dimensional structure of the enzyme has not yet been elucidated, but the active-site residues of human heparanase have been described, and it is widely accepted that there are two essential acidic residues (Glu 225 and Glu 343 ) involved in the catalytic mechanism, acting as a putative proton donor and a nucleophile, respectively [6]. Despite the increasing interest in finding effective inhibitors against heparanase, and although a number of compounds with some inhibitory effect have been descri- bed, only one of them has reached so far the clinical trial phases [7]. Heparanase inhibitors reported until now differ in their chemical nature, origin (from natural products to synthetic compounds found through virtual or experimental screening of chemical libraries) and size (from big heparin- like polymers and oligosaccharide mimetics to small molecules with some ‘‘drug-like’’ features) [8]. Pharmacophore modeling is a useful technique for describing interactions of small molecules with macromo- lecular targets of therapeutic interest [9–11]. The IUPAC Rafael Gozalbes and Silvia Mosule ´n contributed equally to this work. R. Gozalbes Á S. Mosule ´n Á R. J. Carbajo Á A. Pineda-Lucena (&) Structural Biology Laboratory, Department of Medicinal Chemistry, Centro de Investigacio ´n Prı ´ncipe Felipe, Avenida Autopista del Saler 16, 46012 Valencia, Spain e-mail: apineda@cipf.es 123 J Comput Aided Mol Des (2009) 23:555–569 DOI 10.1007/s10822-009-9269-0