Condensin plays crucial roles in chromosome organization and compaction, but the mechanistic basis for its functions remains obscure. We used single-molecule imaging to demonstrate that Saccharomyces cerevisiae condensin is a molecular motor capable of adenosine triphosphate hydrolysis–dependent translocation along double-stranded DNA. Condensin’s translocation activity is rapid and highly processive, with individual complexes traveling an average distance of ≥10 kilobases at a velocity of ~60 base pairs per second. Our results suggest that condensin may take steps comparable in length to its ~50-nanometer coiled-coil subunits, indicative of a translocation mechanism that is distinct from any reported for a DNA motor protein. The finding that condensin is a mechanochemical motor has important implications for understanding the mechanisms of chromosome organization and condensation.

DNA strand exchange plays a central role in genetic recombination across all kingdoms of life, but the physical basis for these reactions remains poorly defined. Using single-molecule imaging, we found that bacterial RecA and eukaryotic Rad51 and Dmc1 all stabilize strand exchange intermediates in precise three-nucleotide steps. Each step coincides with an energetic signature (0.3 kBT) that is conserved from bacteria to humans. Triplet recognition is strictly dependent on correct Watson-Crick pairing. Rad51, RecA, and Dmc1 can all step over mismatches, but only Dmc1 can stabilize mismatched triplets. This finding provides insight into why eukaryotes have evolved a meiosis-specific recombinase. We propose that canonical Watson-Crick base triplets serve as the fundamental unit of pairing interactions during DNA recombination.

While fast folding of small proteins has been relatively well characterized by experiments and theories, much less is known for slow folding of larger proteins, for which recent experiments suggested quite complex and rich folding behaviors. Here, we address how the energy landscape theory can be applied to these slow folding reactions. Combining the perfect-funnel approximation with a multiscale method, we first extended our previous atomic-interaction based coarse grained (AICG) model to take into account local flexibility of protein molecules. Using this model, we then investigated the energy landscapes and folding routes of two proteins with complex topologies: a multidomain protein adenylate kinase (AKE) and a knotted protein 2ouf-knot. In the AKE folding, consistent with experimental results, the kinetic free energy surface showed several substates between the fully unfolded and native states. We characterized the structural features of these substates and transitions among them, finding temperature-dependent multiroute folding. For protein 2ouf-knot, we found that the improved atomic-interaction based coarse-grained model can spontaneously tie a knot and fold the protein with a probability up to 96%. The computed folding rate of the knotted protein was much slower than that of its unknotted counterpart, in agreement with experimental findings. Similar to the AKE case, the 2ouf-knot folding exhibited several substates and transitions among them. Interestingly, we found a dead-end substate that lacks the knot, thus suggesting backtracking mechanisms.

To reduce the number of replicas required in the conventional replica exchange method for huge systems, recently the replica exchange with solute tempering (REST) method was proposed. Here we showed that a variant of REST realized by rescaling the force-field parameters can be performed with GROMACS 4 without changing the code. We tested the variant REST for alanine dipeptide and an N-terminal peptide from p53 confirming its performance nearly equal to the original REST.

Due to hierarchic nature of biomolecular systems, their computational modeling calls for multiscale approaches, in which coarse-grained (CG) simulations are used to address long-time dynamics of large systems. Here, we review recent developments and applications of CG modeling methods, focusing on our methods primarily for proteins, DNA, and their complexes. These methods have been implemented in the CG biomolecular simulator, CafeMol. Our CG model has resolution such that ∼10 non-hydrogen atoms are grouped into one CG particle on average. For proteins, each amino acid is represented by one CG particle. For DNA, one nucleotide is simplified by three CG particles, representing sugar, phosphate, and base. The protein modeling is based on the idea that proteins have a globally funnel-like energy landscape, which is encoded in the structure-based potential energy function. We first describe two representative minimal models of proteins, called the elastic network model and the classic Go̅ model. We then present a more elaborate protein model, which extends the minimal model to incorporate sequence and context dependent local flexibility and nonlocal contacts. For DNA, we describe a model developed by de Pablo's group that was tuned to well reproduce sequence-dependent structural and thermodynamic experimental data for single- and double-stranded DNAs. Protein-DNA interactions are modeled either by the structure-based term for specific cases or by electrostatic and excluded volume terms for nonspecific cases. We also discuss the time scale mapping in CG molecular dynamics simulations. While the apparent single time step of our CGMD is about 10 times larger than that in the fully atomistic molecular dynamics for small-scale dynamics, large-scale motions can be further accelerated by two-orders of magnitude with the use of CG model and a low friction constant in Langevin dynamics. Next, we present four examples of applications. First, the classic Go̅ model was used to emulate one ATP cycle of a molecular motor, kinesin. Second, nonspecific protein-DNA binding was studied by a combination of elaborate protein and DNA models. Third, a transcription factor, p53, that contains highly fluctuating regions was simulated on two perpendicularly arranged DNA segments, addressing intersegmental transfer of p53. Fourth, we simulated structural dynamics of dinucleosomes connected by a linker DNA finding distinct types of internucleosome docking and salt-concentration-dependent compaction. Finally, we discuss many of limitations in the current approaches and future directions. Especially, more accurate electrostatic treatment and a phospholipid model that matches our CG resolutions are of immediate importance.

The tumor suppressor p53 is a transcription factor that searches its cognate sites on DNA. During the search, the roles and interplay of its two DNA binding domains, the folded core domain and the disordered C-terminal domain (CTD), have been controversial. Here, we performed molecular simulations of p53 at various salt concentrations finding that, at physiological salt concentration, p53 diffuses along nonspecific DNA via rotation-uncoupled sliding with its CTD, whereas the core domain repeats dissociation and association. This is in perfect agreement with a recent single molecule experiment. In the simulation of tetrameric full-length p53, two DNA binding domains both bound to nonspecific DNA in a characteristic form at low salt concentration, whereas at physiological salt concentration, only CTD kept bound to DNA and the core domain frequently hopped on DNA. Simulations of a construct that lacks the core domain (TetCD) clarified rotation-uncoupled diffusion on nonspecific DNA. At low salt concentration, the diffusion constant due to sliding was dependent on the salt concentration, which differs from the prediction of a classic theory of transcription factors. At physiological salt concentration, it was independent of the salt concentration, in harmony with experiments. Moreover, we found that the sliding via the CTD follows the helical pitch of DNA (i.e., rotation-coupled sliding) at low salt concentration while it is virtually uncoupled to the helical pitch, a hallmark of rotation-uncoupled sliding at physiological salt concentration.

Intrinsically disordered proteins (IDPs) are ubiquitous and play key roles in transcriptional regulations and other cellular processes. To characterize diverse structural ensembles of IDPs, combinations of NMR and computational modeling showed some promise, but they need further improvements. Here, for accurate and efficient modeling of IDPs, we propose a systematic multiscale computational method. We first perform all-atom replica-exchange molecular dynamics (MD) simulations of a few fragments selected from a target IDP. These results together with generic knowledge-based local potentials are fed into the iterative Boltzmann inversion method to obtain an accurate coarse-grained potential. Then coarse-grained MD simulations provide the IDP ensemble. We tested the new method for the disordered N-terminal domain of p53 showing that the method reproduced the residual dipolar coupling and x-ray scattering profile very accurately. Further local structure analyses revealed that, guided by all-atom MD ensemble of fragments, the p53 N-terminal domain ensemble was biased to kinked structures in the AD1 region and biased to extended conformers in a proline-rich region and these biases contributed to improvement of the reproduction of the experiments.

Protein binding to DNA changes the DNA's structure, and altered DNA structure can, in turn, modulate the dynamics of protein binding. This mutual dependency is poorly understood. Here we investigated dynamic couplings among protein binding to DNA, protein sliding on DNA, and DNA bending by applying a coarse-grained simulation method to the bacterial architectural protein HU and 14 other DNA-binding proteins. First, we verified our method by showing that the simulated HU exhibits a weak preference for A/T-rich regions of DNA and a much higher affinity for gapped and nicked DNA, consistent with biochemical experiments. The high affinity was attributed to a local DNA bend, but not the specific chemical moiety of the gap/nick. The long-time dynamic analysis revealed that HU sliding is associated with the movement of the local DNA bending site. Deciphering single sliding steps, we found the coupling between HU sliding and DNA bending is akin to neither induced-fit nor population-shift; instead they moved concomitantly. This is reminiscent of a cation transfer on DNA and can be viewed as a protein version of polaron-like sliding. Interestingly, on shorter time scales, HU paused when the DNA was highly bent at the bound position and escaped from pauses once the DNA spontaneously returned to a less bent structure. The HU sliding is largely regulated by DNA bending dynamics. With 14 other proteins, we explored the generality and versatility of the dynamic coupling and found that 6 of the 15 assayed proteins exhibit the polaron-like sliding.