Structure-Based Integrative Computational and Experimental Approach for the Optimization of Drug Design*

Dimitrios Morikis1, Christodoulos A. Floudas2, and John D. Lambris3

1Department of Chemical and Environmental Engineering, University of California, Riverside, CA 92521, USA
dmorikis@engr.ucr.edu

2Department of Chemical Engineering, Princeton University, Princeton, NJ 08544, USA
floudas@titan.princeton.edu

3Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA

Abstract. We present an integrative approach for the optimization in the design of peptides which are candidates to become therapeutic agents. This approach is based on the structure of the peptide ligand when structural information on the protein target is not available. Our approach combines (i) NMR spectroscopy, (ii) structure determination by distance geometry, simulated annealing, and global optimization methods, restrained with NMR-derived or deduced restraints, (iii) molecular dynamics simulations, based on NMR low energy, averaged minimized, or ensemble of structures, (iv) in silico sequence selection using integer linear optimization, (v) fold specificity using deterministic global optimization, and (vi) peptide synthesis, mass spectrometry characterization, and activity measurements. The optimization of the design of the 13-residue cyclic peptide compstatin is presented as a paradigm for the application of our approach. The same principles can be applied for the design of small proteins with desired properties and function.

*This work was supported by grants from NIH and NSF.

LNCS 3515, pp. 680-688.

Last modified: