A historical perspective on the application of molecular dynamics (MD) to biological macromolecules is presented. Recent developments combining state-of-the-art force fields with continuum solvation calculations have allowed us to reach the fourth era of MD applications in which one can often derive both accurate structure and accurate relative free energies from molecular dynamics trajectories. We illustrate such applications on nucleic acid duplexes, RNA hairpins, protein folding trajectories, and proteinligand, protein-protein, and protein-nucleic acid interactions.

The MM-PBSA (Molecular Mechanics-Poisson-Boltzmann surface area) method was applied to the human Growth Hormone (hGH) complexed with its receptor to assess both the validity and the limitations of the computational alanine scanning approach. A 400-ps dynamical trajectory of the fully solvated complex was simulated at 300 K in a 101 A x 81 A x 107 A water box using periodic boundary conditions. Long-range electrostatic interactions were treated with the particle mesh Ewald (PME) summation method. Equally spaced snapshots along the trajectory were chosen to compute the binding free energy using a continuum solvation model to calculate the electrostatic desolvation free energy and a solvent-accessible surface area approach to treat the nonpolar solvation free energy. Computational alanine scanning was performed on the same set of snapshots by mutating the residues in the structural epitope of the hormone and the receptor to alanine and recomputing the deltaGbinding. To further investigate a particular structure, a 200-ps dynamical trajectory of an R43A hormone-receptor complex was simulated. By postprocessing a single trajectory of the wild-type complex, the average unsigned error of our calculated deltadeltaGbinding is approximately1 kcal/mol for the alanine mutations of hydrophobic residues and polar/charged residues without buried salt bridges. When residues involved in buried salt bridges are mutated to alanine, it is demonstrated that a separate trajectory of the alanine mutant complex can lead to reasonable agreement with experimental results. Our approach can be extended to rapid screening of a variety of possible modifications to binding sites.

We have developed a fast procedure to predict solvation free energies for both organic and biological molecules. This solvation model is based on weighted solvent accessible surface area (WSAS). Least-squares fittings have been applied to optimize the weights of SAS for different atom types in order to reproduce the experimental solvation free energies. Good agreement with experimental results has been obtained. For the 184-molecule set (model I), for which there are experimental solvation free energies in 1-octanol, we have achieved an average error of 0.36 kcal/mol, better than that of the SM5.42R universal solvation model 1 by Li et al. For the 245-molecule set (model II) that has experimental aqueous solvation free energies, our WSAS model achieves an average error of 0.48 kcal/mol, marginally larger than that of Li's model (0.46 kcal/mol). We have used a 401-molecule set, the largest training set (model IV) that we know of solvation model development, to derive the SAS weights in order to reproduce the experimental solvation free energies in water. For this model, we have achieved an average unsigned error of 0.54 kcal/mol and an RMS error of 0.79 kcal/mol.The advantage of this model lies in its simplicity and independence of charge models. We have successfully applied this model to predict the relative binding free energies for the five binding modes of HIV-1RT/ efavirenz. The most favorable binding mode, which has an RMSD of 1.1 Å (for 54 C R around the binding site) compared to the crystal structure, has a binding free energy at least 10 kcal/mol more negative than the other binding modes. Moreover, the solvation free energies with WSAS have a high correlation (the correlation coefficient is 0.92) to the solvation free energies calculated by the Poisson-Boltzmann/surface area (PBSA) model. As an efficient and fast approach, WASA is also attractive for protein modeling and protein folding studies. We have applied this model to predict the solvation free energies of the 36-mer villin headpiece subdomain in its native structure, a compact folding intermediate, and a random coil. The rank order of the solvation free energies and the free energies for the three kinds of conformational clusters are in reasonable agreement with those found by MM-PBSA, a widely used solvation free energy model.