title: Structure modeling, ligand binding, and binding affinity calculation (LR-MM-PBSA) of human heparanase for inhibition and drug design.
abstract: Human heparanase is an endo-beta-D-glycosidase that cleaves heparan sulphate (HS) chains in the extracellular matrix and basement membrane. It is known that the cleavage of HS by heparanase results in cell invasion and metastasis of cancer. Therefore, heparanase is considered an important target for cancer drug development. The three-dimensional structure of heparanase would be useful in the rational design of inhibitors targeted to the enzyme; however, the three-dimensional structure has not yet been determined. In our effort to design inhibitors, we developed a three-dimensional structure of heparanase using a homology-modeling approach. The homology-built structure is consistent to previous bioinformatics and site-mutation experimental results. The heparanase features a (alpha/beta)(8) TIM-barrel fold with two glutamate residues (Glu225 and Glu343) located in the active-site cleft. This feature supports the putative mechanism of proton donor and nucleophilic sites. Docking simulations yielded 41 complex structures, which indicate that the bound inhibitor could block ligand binding into the catalytic site. A free energy of binding model was established for 25 heparanase inhibitors with a training set of 25 heparanase inhibitors using the linear response MM-PBSA approach (LR-MM-PBSA). The correlation between calculated and experimental activity was 0.79 and the reliability of the model was validated with leave-one-out cross-validation method. Its predictive capability was further validated using a test set of 16 inhibitors similar to the training set of inhibitors. The correlation between the predicted and observed activities is significantly improved by the protein "induced-fit" that accounts for the flexibility of the receptor. These interaction and pharmacophore elements provide a unique insight to the rational design of new ligands targeted to the enzyme.
authors.affiliation: Department of Chemistry and Biochemistry, Duquesne University, Pittsburgh, Pennsylvania 15213, USA. zhou@purdue.edu
authors.forename: Zhigang
authors.initials: Z
authors.lastname: Zhou
authors.forename: Maria
authors.initials: M
authors.lastname: Bates
authors.forename: Jeffry D
authors.initials: JD
authors.lastname: Madura
mesh_terms: D000595:Amino Acid Sequence; D001665:Binding Sites; D002384:Catalysis; D003198:Computer Simulation; D015195:Drug Design; D004791:Enzyme Inhibitors / Q000737:chemistry*; D005966:Glucuronidase / Q000037:antagonists & inhibitors / Q000737:chemistry*; D006801:Humans; D006860:Hydrogen Bonding; D008024:Ligands; D008958:Models, Molecular; D008969:Molecular Sequence Data; D017433:Protein Structure, Secondary; D016415:Sequence Alignment; D040681:Structural Homology, Protein; D013329:Structure-Activity Relationship; D013816:Thermodynamics; D000099175:Heparanase
chemical_list: D004791:Enzyme Inhibitors; D005966:Glucuronidase; D008024:Ligands; D000099175:Heparanase