Free-Energy Calculations Highlight Differences in Accuracy between X-Ray and NMR Structures and Add Value to Protein Structure Prediction

AbstractBackground: While X-ray crystallography structures of proteins are considerably more reliable than those from NMR spectroscopy, it has been difficult to assess the inherent accuracy of NMR structures, particularly the side chains.Results: For 15 small single-domain proteins, we used a molecular mechanics-/dynamics-based free-energy approach to investigate native, decoy, and fully extended alpha conformations. Decoys were all less energetically favorable than native conformations in nine of the ten X-ray structures and in none of the five NMR structures, but short 150 ps molecular dynamics simulations on the experimental structures caused them to have the lowest predicted free energy in all 15 proteins. In addition, a strong correlation exists (r2 = 0.86) between the predicted free energy of unfolding, from native to fully extended conformations, and the number of residues.Conclusions: This work suggests that the approximate treatment of solvent used in solving NMR structures can lead NMR model conformations to be less reliable than crystal structures. This conclusion was reached because of the considerably higher calculated free energies and the extent of structural deviation during aqueous dynamics simulations of NMR models compared to those determined by X-ray crystallography. Also, the strong correlation found between protein length and predicted free energy of unfolding in this work suggests, for the first time, that a free-energy function can allow for identification of the native state based on calculations on an extended state and in the absence of an experimental structure

Wang-Landau molecular dynamics technique to search for low-energy conformational space of proteins

Multicanonical molecular dynamics (MD) is a powerful technique for sampling conformations on rugged potential surfaces such as protein. However, it is notoriously difficult to estimate the multicanonical temperature effectively. Wang and Landau developed a convenient method for estimating the density of states based on a multicanonical Monte Carlo method. In their method, the density of states is calculated autonomously during a simulation. In this paper we develop a set of techniques to effectively apply the Wang-Landau method to MD simulations. In the multicanonical MD, the estimation of the derivative of the density of states is critical. In order to estimate it accurately, we devise two original improvements. First, the correction for the density of states is made smooth by using the Gaussian distribution obtained by a short canonical simulation. Second, an approximation is applied to the derivative, which is based on the Gaussian distribution and the multiple weighted histogram technique. A test of this method was performed with small polypeptides, Met-enkephalin and Trp-cage, and it is demonstrated that Wang-Landau MD is consistent with replica exchange MD but can sample much larger conformational space.Comment: 8 pages, 7 figures, accepted for publication in Physical Review

Interaction of CK1δ with γTuSC ensures proper microtubule assembly and spindle positioning.

Casein kinase 1δ (CK1δ) family members associate with microtubule-organizing centers (MTOCs) from yeast to humans, but their mitotic roles and targets have yet to be identified. We show here that budding yeast CK1δ, Hrr25, is a γ-tubulin small complex (γTuSC) binding factor. Moreover, Hrr25's association with γTuSC depends on its kinase activity and its noncatalytic central domain. Loss of Hrr25 kinase activity resulted in assembly of unusually long cytoplasmic microtubules and defects in spindle positioning, consistent with roles in regulation of γTuSC-mediated microtubule nucleation and the Kar9 spindle-positioning pathway, respectively. Hrr25 directly phosphorylated γTuSC proteins in vivo and in vitro, and this phosphorylation promoted γTuSC integrity and activity. Because CK1δ and γTuSC are highly conserved and present at MTOCs in diverse eukaryotes, similar regulatory mechanisms are expected to apply generally in eukaryotes

Theory of Systematic Computational Error in Free Energy Differences

Systematic inaccuracy is inherent in any computational estimate of a non-linear average, due to the availability of only a finite number of data values, N. Free energy differences (DF) between two states or systems are critically important examples of such averages in physical, chemical and biological settings. Previous work has demonstrated, empirically, that the ``finite-sampling error'' can be very large -- many times kT -- in DF estimates for simple molecular systems. Here, we present a theoretical description of the inaccuracy, including the exact solution of a sample problem, the precise asymptotic behavior in terms of 1/N for large N, the identification of universal law, and numerical illustrations. The theory relies on corrections to the central and other limit theorems, and thus a role is played by stable (Levy) probability distributions.Comment: 5 pages, 4 figure

Differential role for trehalose metabolism in salt-stressed maize

Little is known about how salt impacts primary metabolic pathways of C4 plants, particularly related to kernel development and seed set. Osmotic stress was applied to maize (Zea mays) B73 by irrigation with increasing concentrations of NaCl from the initiation of floral organs until 3 d after pollination. At silking, photosynthesis was reduced to only 2% of control plants. Salt treatment was found to reduce spikelet growth, silk growth, and kernel set. Osmotic stress resulted in higher concentrations of sucrose (Suc) and hexose sugars in leaf, cob, and kernels at silking, pollination, and 3 d after pollination. Citric acid cycle intermediates were lower in salt-treated tissues, indicating that these sugars were unavailable for use in respiration. The sugar-signaling metabolite trehalose-6-phosphate was elevated in leaf, cob, and kernels at silking as a consequence of salt treatment but decreased thereafter even as Suc levels continued to rise. Interestingly, the transcripts of trehalose pathway genes were most affected by salt treatment in leaf tissue. On the other hand, transcripts of the SUCROSE NONFERMENTING-RELATED KINASE1 (SnRK1) marker genes were most affected in reproductive tissue. Overall, both source and sink strength are reduced by salt, and the data indicate that trehalose-6-phosphate and SnRK1 may have different roles in source and sink tissues. Kernel abortion resulting from osmotic stress is not from a lack of carbohydrate reserves but from the inability to utilize these energy reserves

Modelling societal transitions with agent transformation

Transition models explain long-term and large-scale processes fundamentally changing the structure of a societal system. Our concern is that most transition models are too static. Although they capture a move of focus from static equilibria to transitions between dynamic equilibria, they are still rooted in an "equilibriumist" approach. Improvement is possible with agent-based models that give attention to endogenous system processes called "transformation processes". These models can render far more dynamic pictures of societal systems in transition, and are no longer remote from descriptions in the emerging transition literature

Efficient Passive ICS Device Discovery and Identification by MAC Address Correlation

Owing to a growing number of attacks, the assessment of Industrial Control Systems (ICSs) has gained in importance. An integral part of an assessment is the creation of a detailed inventory of all connected devices, enabling vulnerability evaluations. For this purpose, scans of networks are crucial. Active scanning, which generates irregular traffic, is a method to get an overview of connected and active devices. Since such additional traffic may lead to an unexpected behavior of devices, active scanning methods should be avoided in critical infrastructure networks. In such cases, passive network monitoring offers an alternative, which is often used in conjunction with complex deep-packet inspection techniques. There are very few publications on lightweight passive scanning methodologies for industrial networks. In this paper, we propose a lightweight passive network monitoring technique using an efficient Media Access Control (MAC) address-based identification of industrial devices. Based on an incomplete set of known MAC address to device associations, the presented method can guess correct device and vendor information. Proving the feasibility of the method, an implementation is also introduced and evaluated regarding its efficiency. The feasibility of predicting a specific device/vendor combination is demonstrated by having similar devices in the database. In our ICS testbed, we reached a host discovery rate of 100% at an identification rate of more than 66%, outperforming the results of existing tools.Comment: http://dx.doi.org/10.14236/ewic/ICS2018.

P1‐504: Influence Of Patient Mci On Physician Conception Of Risk And Decision‐Making For Cardiovascular Treatments

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/153216/1/alzjjalz2019061109.pd