Hybrid computational methods for combining structural data from different sources and resolutions are becoming an essential part of structural biology, especially as the field moves toward the study of large macromolecular assemblies. We have developed the molecular dynamics flexible fitting (MDFF) method for combining high-resolution atomic structures with cryo-electron microscopy (cryo-EM) maps, that results in atomic models representing the conformational state captured by cryo-EM. The method has been applied successfully to the ribosome, a ribonucleoprotein complex responsible for protein synthesis. MDFF involves a molecular dynamics simulation in which a guiding potential, based on the cryo-EM map, is added to the standard force field. Forces proportional to the gradient of the density map guide an atomic structure, available from X-ray crystallography, into high-density regions of a cryo-EM map. In this paper we describe the necessary steps to set up, run, and analyze MDFF simulations and the software packages that implement the corresponding functionalities.

Experimental studies of protein folding processes are frequently hampered by the fact that only low resolution structural data can be obtained with sufficient temporal resolution. Molecular dynamics simulations offer a complementary approach, providing extremely high resolution spatial and temporal data on folding processes. The effectiveness of such simulations is currently hampered by continuing questions regarding the ability of molecular dynamics force fields to reproduce the true potential energy surfaces of proteins, and ongoing difficulties with obtaining sufficient sampling to meaningfully comment on folding mechanisms. We review recent progress in the simulation of three common model systems for protein folding, and discuss how recent advances in technology and theory are allowing protein folding simulations to address their current shortcomings.

The development of class- and isoform-selective histone deacetylase (HDAC) inhibitors is highly desirable for the study of the complex interactions of these proteins central to transcription regulation as well as for the development of selective HDAC inhibitors as drugs in epigenetics. To provide a structural basis for the rational design of such inhibitors, a combined computational and experimental study of inhibition of three different histone deacetylase isoforms, HDAC1, -6, and -8, with three different hydroxamate inhibitors is reported. While SAHA was found to be unselective for the inhibition of class I and class II HDACs, the other inhibitors were found to be selective toward class II HDACs. Molecular dynamics simulations indicate that this selectivity is caused by both the overall shape of the protein surface leading to the active site and specific interactions of an aspartate residue in a polar loop and two phenylalanines and a methionine in a nonpolar loop. Monitoring the specific interactions as a function of the simulation time identifies a key sulfur-pi interaction. The implications of the structural motifs for the design of class II-selective HDAC inhibitors are discussed.

Accelerated molecular dynamics (aMD) is an enhanced-sampling method that improves the conformational space sampling by reducing energy barriers separating different states of a system. Here we present the implementation of aMD in the parallel simulation program NAMD. We show that aMD simulations performed with NAMD have only a small overhead compared with classical MD simulations. Through example applications to the alanine dipeptide, we discuss the choice of acceleration parameters, the interpretation of aMD results, as well as the advantages and limitations of the aMD method.