Computational methods currently play a significant role in the discovery of new pharmaceuticals. When the structure of the target or a closely related protein is known, computational prediction of binding affinities may be employed as part of lead discovery or optimization efforts. For protein targets with unknown structures, various computational methods have been developed in order to accurately predict their tertiary structures. This work summarizes the three computational chemistry projects I worked on, including membrane protein structure prediction, free energy calculation method and polarizable force field development.
In Chapter 2, we evaluate the scoring function accuracy for membrane protein structure prediction. We perform a systematic examination of the ability of several different high-resolution; atomic-detail scoring functions to discriminate native conformations of loops in membrane proteins from non-native but physically reasonable, or decoy, conformations. Decoys constructed from changing a loop conformation while keeping the remainder of the protein fixed are a challenging test of energy function accuracy. Nevertheless, the best of the energy functions we examined recognized the native structure as lowest in energy around half the time, and consistently chose it as a low-energy structure. This suggests that the best of present energy functions, even without a representation of the lipid bilayer, are of sufficient accuracy to give reasonable confidence in predictions of membrane protein structure. We also constructed homology models for each structure, using other known structures in the same protein family as templates. Homology models were constructed using several scoring functions and modeling programs, but with a comparable sampling effort for each procedure. Our results indicate that the quality of sequence alignment is probably the most important factor in model accuracy for sequence identity from 20-40%; one can expect a reasonably accurate model for membrane proteins when sequence identity is greater than 30%, in agreement with previous studies. Most errors are localized in loop regions, which tend to be found outside the lipid bilayer. For the most discriminative energy functions, it appears that errors are most likely due to lack of sufficient sampling, although it should be stressed that present energy functions are still far from perfectly reliable.
In Chapter 3, we present a method for estimating the free energy change due to the ligand conformational changes upon binding, based on perturbation theory using the quasiharmonic model of Karplus and Kushick as a reference system. The consistency of the method is checked for small model systems. The method was then applied to calculate relative affinities for a set of 233 protein-ligand complexes for which crystal structures and measured binding affinities are available, using the generalized AMBER force field and generalized Born implicit solvent model. In most cases, the ligand conformation in the bound state was significantly different from the most favorable conformation in solution. In general, the correlation between measured and calculated ligand binding affinities including the free energy change due to ligand conformational change is comparable to or slightly better than that obtained by using an empirically-trained docking score. Both entropic and enthalpic contributions to this free energy change are significant.
In Chapter 4, the preliminary work to parameterize a force field incorporating an explicit representation of polarizability is presented. This polarizable charge model, in the form of fluctuating bond-charge increments, is parameterized using the Mulliken charges taken from density functional theory (DFT) calculations in both vacuum and crystalline phases. During the fitting process, several restraints are incorporated, including dipole moment restraints for gas-phase molecules and structure factor restraints for bulk crystals. The weights of each restraint are examined. A detailed charge fitting procedure is included at the end of this chapter.