Fragment and protein simulation methods in fragment based drug design

Fragment-based drug design (FBDD) has become an important and successful approach to drug discovery. In this review, we discuss two classes of simulation technologies that we routinely employ as part our of computational FBDD efforts. The first class centers on simulation methods in torsion space to develop high-quality protein models suitable for FBDD. These algorithms allow for fast molecular dynamics and modal Monte Carlo simulations. The torsion space dynamics techniques have been applied to develop models for the bound conformations of a variety of proteins including the HIV-1 protease, p38 MAP kinase, and the 5′-AMP-activated protein kinase. The second class of simulations is comprised of the Grand Canonical Monte Carlo and systematic sampling methods, which are used to explore the interactions of individual fragments with the protein target. Previously published validation studies for the binding of molecules to T4 lysozyme and the p38 MAP kinase are discussed. We review previous work to computationally assemble whole molecules from fragment binding data, a potential bottleneck in the FBDD approach. One effect of the fragment simulations is that an approximate value for the free energy of binding of a given molecule with the protein may be computed from the fragment simulations, with an estimated standard error approaching 1 kcal/mol, which is comparable to the performance of a variety of other methods reported in the literature. Drug Dev Res 72:130–137, 2011.  © 2010 Wiley-Liss, Inc.