Competition between Stacking and Divalent Cation-Mediated Electrostatic Interactions Determines the Conformations of Short DNA Sequences.

Interplay between divalent cations (Mg2+ and Ca2+) and single-stranded DNA (ssDNA) and double-stranded DNA (dsDNA), as well as stacking interactions, is important in nucleosome stability and phase separation in nucleic acids. Quantitative techniques accounting for ion-DNA interactions are needed to obtain insights into these and related problems. Toward this end, we created a sequence-dependent computational TIS-ION model that explicitly accounts for monovalent and divalent ions. Simulations of the rigid 24 base-pair (bp) dsDNA and flexible ssDNA sequences, dT30 and dA30, with varying amounts of the divalent cations show that the calculated excess number of ions around the dsDNA and ssDNA agree quantitatively with ion-counting experiments. Using an ensemble of all-atom structures generated from coarse-grained simulations, we calculated the small-angle X-ray scattering profiles, which are in excellent agreement with experiments. Although ion-counting experiments mask the differences between Mg2+ and Ca2+, we find that Mg2+ binds to the minor grooves and phosphate groups, whereas Ca2+ binds specifically to the minor groove. Both Mg2+ and Ca2+ exhibit a tendency to bind to the minor groove of DNA as opposed to the major groove. The dA30 conformations are dominated by stacking interactions, resulting in structures with considerable helical order. The near cancellation of the favorable stacking and unfavorable electrostatic interactions leads to dT30 populating an ensemble of heterogeneous conformations. The successful applications of the TIS-ION model are poised to confront many problems in DNA biophysics.

Brewing COFFEE: A Sequence-Specific Coarse-Grained Energy Function for Simulations of DNA-Protein Complexes.

DNA-protein interactions are pervasive in a number of biophysical processes ranging from transcription and gene expression to chromosome folding. To describe the structural and dynamic properties underlying these processes accurately, it is important to create transferable computational models. Toward this end, we introduce Coarse-grained Force Field for Energy Estimation, COFFEE, a robust framework for simulating DNA-protein complexes. To brew COFFEE, we integrated the energy function in the self-organized polymer model with side-chains for proteins and the three interaction site model for DNA in a modular fashion, without recalibrating any of the parameters in the original force-fields. A unique feature of COFFEE is that it describes sequence-specific DNA-protein interactions using a statistical potential (SP) derived from a data set of high-resolution crystal structures. The only parameter in COFFEE is the strength (λDNAPRO) of the DNA-protein contact potential. For an optimal choice of λDNAPRO, the crystallographic B-factors for DNA-protein complexes with varying sizes and topologies are quantitatively reproduced. Without any further readjustments to the force-field parameters, COFFEE predicts scattering profiles that are in quantitative agreement with small-angle X-ray scattering experiments, as well as chemical shifts that are consistent with NMR. We also show that COFFEE accurately describes the salt-induced unraveling of nucleosomes. Strikingly, our nucleosome simulations explain the destabilization effect of ARG to LYS mutations, which do not alter the balance of electrostatic interactions but affect chemical interactions in subtle ways. The range of applications attests to the transferability of COFFEE, and we anticipate that it would be a promising framework for simulating DNA-protein complexes at the molecular length-scale.

Brewing COFFEE: A sequence-specific coarse-grained energy function for simulations of DNA-protein complexes.

DNA-protein interactions are pervasive in a number of biophysical processes ranging from transcription, gene expression, to chromosome folding. To describe the structural and dynamic properties underlying these processes accurately, it is important to create transferable computational models. Toward this end, we introduce Coarse grained force field for energy estimation, COFFEE, a robust framework for simulating DNA-protein complexes. To brew COFFEE, we integrated the energy function in the Self-Organized Polymer model with Side Chains for proteins and the Three Interaction Site model for DNA in a modular fashion, without re-calibrating any of the parameters in the original force-fields. A unique feature of COFFEE is that it describes sequence-specific DNA-protein interactions using a statistical potential (SP) derived from a dataset of high-resolution crystal structures. The only parameter in COFFEE is the strength (λDNAPRO) of the DNA-protein contact potential. For an optimal choice of λDNAPRO, the crystallographic B-factors for DNA-protein complexes, with varying sizes and topologies, are quantitatively reproduced. Without any further readjustments to the force-field parameters, COFFEE predicts the scattering profiles that are in quantitative agreement with SAXS experiments as well as chemical shifts that are consistent with NMR. We also show that COFFEE accurately describes the salt-induced unraveling of nucleosomes. Strikingly, our nucleosome simulations explain the destabilization effect of ARG to LYS mutations, which does not alter the balance of electrostatic interactions, but affects chemical interactions in subtle ways. The range of applications attests to the transferability of COFFEE, and we anticipate that it would be a promising framework for simulating DNA-protein complexes at the molecular length-scale.

Energy Landscape of Ubiquitin Is Weakly Multidimensional.

Single molecule pulling experiments report time-dependent changes in the extension (X) of a biomolecule as a function of the applied force (f). By fitting the data to one-dimensional analytical models of the energy landscape, we can extract the hopping rates between the folded and unfolded states in two-state folders as well as the height and the location of the transition state (TS). Although this approach is remarkably insightful, there are cases for which the energy landscape is multidimensional (catch bonds being the most prominent). To assess if the unfolding energy landscape in small single domain proteins could be one-dimensional, we simulated force-induced unfolding of ubiquitin (Ub) using the coarse-grained self-organized polymer-side chain (SOP-SC) model. Brownian dynamics simulations using the SOP-SC model reveal that the Ub energy landscape is weakly multidimensional (WMD), governed predominantly by a single barrier. The unfolding pathway is confined to a narrow reaction pathway that could be described as diffusion in a quasi-1D X-dependent free energy profile. However, a granular analysis using the Pfold analysis, which does not assume any form for the reaction coordinate, shows that X alone does not account for the height and, more importantly, the location of the TS. The f-dependent TS location moves toward the folded state as f increases, in accord with the Hammond postulate. Our study shows that, in addition to analyzing the f-dependent hopping rates, the transition state ensemble must also be determined without resorting to X as a reaction coordinate to describe the unfolding energy landscapes of single domain proteins, especially if they are only WMD.

Double Domain Swapping in Human γC and γD Crystallin Drives Early Stages of Aggregation.

Human γD (HγD) and γC (HγC) are two-domain crystallin (Crys) proteins expressed in the nucleus of the eye lens. Structural perturbations in the protein often trigger aggregation, which eventually leads to cataract. To decipher the underlying molecular mechanism, it is important to characterize the partially unfolded conformations, which are aggregation-prone. Using a coarse grained protein model and molecular dynamics simulations, we studied the role of on-pathway folding intermediates in the early stages of aggregation. The multidimensional free energy surface revealed at least three different folding pathways with the population of partially structured intermediates. The two dominant pathways confirm sequential folding of the N-terminal [Ntd] and the C-terminal domains [Ctd], while the third, least favored, pathway involves intermediates where both the domains are partially folded. A native-like intermediate (I*), featuring the folded domains and disrupted interdomain contacts, gets populated in all three pathways. I* forms domain swapped dimers by swapping the entire Ntds and Ctds with other monomers. Population of such oligomers can explain the increased resistance to unfolding resulting in hysteresis observed in the folding experiments of HγD Crys. An ensemble of double domain swapped dimers are also formed during refolding, where intermediates consisting of partially folded Ntds and Ctds swap secondary structures with other monomers. The double domain swapping model presented in our study provides structural insights into the early events of aggregation in Crys proteins and identifies the key secondary structural swapping elements, where introducing mutations will aid in regulating the overall aggregation propensity.

Cosolvent effects on the growth of amyloid fibrils.

Cells are equipped with cosolvents that modulate protein folding and aggregation to withstand water stress. The effect of cosolvents on the aggregation rates depends on whether the polypeptide sequence is an intrinsically disordered protein (IDP) or can fold into a specific native structure. Cosolvents, which act as denaturants generally slow down aggregation in IDPs, while expediting it in globular proteins. In contrast, protecting osmolytes facilitate aggregation in IDPs, while slowing it down in globular proteins. In this review we highlight the recent computational approaches to gain insight into the role of cosolvents on the aggregation mechanism of IDPs and globular proteins. Computer simulations using the molecular transfer model, which implements the cosolvent effects in coarse-grained protein models in conjunction with enhanced sampling techniques played an important role in elucidating the effect of cosolvents on the growth of amyloid fibrils.

A Transient Intermediate Populated in Prion Folding Leads to Domain Swapping.

Aggregation of misfolded prion proteins causes fatal neurodegenerative disorders in both humans and animals. There is an extensive effort to identify the elusive aggregation-prone conformations (N*) of prions, which are early stage precursors to aggregation. We studied temperature- and force-induced unfolding of the structured C-terminal domain of mouse (moPrP) and human prion proteins (hPrP) using molecular dynamics simulations and coarse-grained protein models. We find that these proteins sparsely populate intermediate states bearing the features of N* and readily undergo domain-swapped dimerization by swapping the short ß-strands present at the beginning of the C-terminal domain. The structure of the N* state is similar for both moPrP and hPrP, indicating a common pathogenic precursor across different species. Interestingly, disease-resistant hPrP (G127V) showed a drastic reduction in the population of the N* state further hinting a pathogenic connection to these partially denatured conformations. This study proposes a plausible runaway domain-swapping mechanism to describe the onset of prion aggregation.

Cosolvent Effects on the Growth of Protein Aggregates Formed by a Single Domain Globular Protein and an Intrinsically Disordered Protein.

Cosolvents modulate the stability of protein conformations and exhibit contrasting effects on the kinetics of aggregation by globular proteins and intrinsically disordered proteins (IDPs). The growth of ordered protein aggregates after the initial nucleation step is believed to proceed through a dock-lock mechanism. We have studied the effect of two denaturants [guanidinium chloride (GdmCl) and urea] and four protective osmolytes (trimethylamine N-oxide (TMAO), sucrose, sarcosine, and sorbitol) on the free energy surface (FES) of the dock-lock growth step of protein aggregation using a coarse-grained protein model and metadynamics simulations. We have used the proteins cSrc-SH3 and Aß9-40 as model systems representing globular proteins and IDPs, respectively. The effect of cosolvents on protein conformations is taken into account using the molecular transfer model (MTM). The computed FES shows that protective osmolytes stabilize the compact aggregates, while denaturants destabilize them for both cSrc-SH3 and Aß9-40. However, protective osmolytes increase the effective energy barrier for the multistep domain-swapped dimerization of cSrc-SH3, which is critical to the growth of protein aggregates by globular proteins, thus slowing down the overall aggregation rate. Contrastingly, denaturants decrease the effective barrier height for cSrc-SH3 dimerization and hence enhance the aggregation rate in globular proteins. The simulations further show that cSrc-SH3 monomers unfold before dimerization and the barrier to monomer unfolding regulates the effective rate of aggregation. In the case of IDP, Aß9-40, protective osmolytes decrease and denaturants increase the effective barriers in the dock-lock mechanism of fibril growth, leading to faster and slower growth kinetics, respectively.