Protein dynamics with off-lattice Monte Carlo moves

A Monte Carlo method for dynamics simulation of all-atom protein models is introduced, to reach long times not accessible to conventional molecular dynamics. The considered degrees of freedom are the dihedrals at C$_\alpha$-atoms. Two Monte Carlo moves are used: single rotations about torsion axes, and cooperative rotations in windows of amide planes, changing the conformation globally and locally, respectively. For local moves Jacobians are used to obtain an unbiased distribution of dihedrals. A molecular dynamics energy function adapted to the protein model is employed. A polypeptide is folded into native-like structures by local but not by global moves.Comment: 10 pages, 4 Postscript figures, uses epsf.sty and a4.sty; scheduled tentatively for Phys.Rev.E issue of 1 March 199

Terahertz underdamped vibrational motion governs protein-ligand binding in solution

Low-frequency collective vibrational modes in proteins have been proposed as being responsible for efficiently directing biochemical reactions and biological energy transport. However, evidence of the existence of delocalized vibrational modes is scarce and proof of their involvement in biological function absent. Here we apply extremely sensitive femtosecond optical Kerr-effect spectroscopy to study the depolarized Raman spectra of lysozyme and its complex with the inhibitor triacetylchitotriose in solution. Underdamped delocalized vibrational modes in the terahertz frequency domain are identified and shown to blue-shift and strengthen upon inhibitor binding. This demonstrates that the ligand-binding coordinate in proteins is underdamped and not simply solvent-controlled as previously assumed. The presence of such underdamped delocalized modes in proteins may have significant implications for the understanding of the efficiency of ligand binding and protein–molecule interactions, and has wider implications for biochemical reactivity and biological function

R2R - software to speed the depiction of aesthetic consensus RNA secondary structures

<p>Abstract</p> <p>Background</p> <p>With continuing identification of novel structured noncoding RNAs, there is an increasing need to create schematic diagrams showing the consensus features of these molecules. RNA structural diagrams are typically made either with general-purpose drawing programs like Adobe Illustrator, or with automated or interactive programs specific to RNA. Unfortunately, the use of applications like Illustrator is extremely time consuming, while existing RNA-specific programs produce figures that are useful, but usually not of the same aesthetic quality as those produced at great cost in Illustrator. Additionally, most existing RNA-specific applications are designed for drawing single RNA molecules, not consensus diagrams.</p> <p>Results</p> <p>We created R2R, a computer program that facilitates the generation of aesthetic and readable drawings of RNA consensus diagrams in a fraction of the time required with general-purpose drawing programs. Since the inference of a consensus RNA structure typically requires a multiple-sequence alignment, the R2R user annotates the alignment with commands directing the layout and annotation of the RNA. R2R creates SVG or PDF output that can be imported into Adobe Illustrator, Inkscape or CorelDRAW. R2R can be used to create consensus sequence and secondary structure models for novel RNA structures or to revise models when new representatives for known RNA classes become available. Although R2R does not currently have a graphical user interface, it has proven useful in our efforts to create 100 schematic models of distinct noncoding RNA classes.</p> <p>Conclusions</p> <p>R2R makes it possible to obtain high-quality drawings of the consensus sequence and structural models of many diverse RNA structures with a more practical amount of effort. R2R software is available at <url>http://breaker.research.yale.edu/R2R</url> and as an Additional file.</p

Transcriptional Profiling of the Dose Response: A More Powerful Approach for Characterizing Drug Activities

The dose response curve is the gold standard for measuring the effect of a drug treatment, but is rarely used in genomic scale transcriptional profiling due to perceived obstacles of cost and analysis. One barrier to examining transcriptional dose responses is that existing methods for microarray data analysis can identify patterns, but provide no quantitative pharmacological information. We developed analytical methods that identify transcripts responsive to dose, calculate classical pharmacological parameters such as the EC50, and enable an in-depth analysis of coordinated dose-dependent treatment effects. The approach was applied to a transcriptional profiling study that evaluated four kinase inhibitors (imatinib, nilotinib, dasatinib and PD0325901) across a six-logarithm dose range, using 12 arrays per compound. The transcript responses proved a powerful means to characterize and compare the compounds: the distribution of EC50 values for the transcriptome was linked to specific targets, dose-dependent effects on cellular processes were identified using automated pathway analysis, and a connection was seen between EC50s in standard cellular assays and transcriptional EC50s. Our approach greatly enriches the information that can be obtained from standard transcriptional profiling technology. Moreover, these methods are automated, robust to non-optimized assays, and could be applied to other sources of quantitative data

A Self-Organizing Algorithm for Modeling Protein Loops

Protein loops, the flexible short segments connecting two stable secondary structural units in proteins, play a critical role in protein structure and function. Constructing chemically sensible conformations of protein loops that seamlessly bridge the gap between the anchor points without introducing any steric collisions remains an open challenge. A variety of algorithms have been developed to tackle the loop closure problem, ranging from inverse kinematics to knowledge-based approaches that utilize pre-existing fragments extracted from known protein structures. However, many of these approaches focus on the generation of conformations that mainly satisfy the fixed end point condition, leaving the steric constraints to be resolved in subsequent post-processing steps. In the present work, we describe a simple solution that simultaneously satisfies not only the end point and steric conditions, but also chirality and planarity constraints. Starting from random initial atomic coordinates, each individual conformation is generated independently by using a simple alternating scheme of pairwise distance adjustments of randomly chosen atoms, followed by fast geometric matching of the conformationally rigid components of the constituent amino acids. The method is conceptually simple, numerically stable and computationally efficient. Very importantly, additional constraints, such as those derived from NMR experiments, hydrogen bonds or salt bridges, can be incorporated into the algorithm in a straightforward and inexpensive way, making the method ideal for solving more complex multi-loop problems. The remarkable performance and robustness of the algorithm are demonstrated on a set of protein loops of length 4, 8, and 12 that have been used in previous studies

The Marshall Grazing Incidence X-ray Spectrometer (MaGIXS)

The Marshall Grazing Incidence X-ray Spectrometer (MaGIXS) is a sounding rocket instrument that flew on July 30, 2021 from the White Sands Missile Range, NM. The instrument was designed to address specific science questions that require differential emission measures of the solar soft X-ray spectrum from 6 – 25[Formula: see text]Å(0.5 – 2.1[Formula: see text]keV). MaGIXS comprises a Wolter-I telescope, a slit-jaw imaging system, an identical pair of grazing incidence paraboloid mirrors, a planar grating and a CCD camera. While implementing this design, some limitations were encountered in the production of the X-ray mirrors, which ended up as a catalyst for the development of a deterministic polishing approach and an improved meteorological technique that utilizes a computer-generated hologram (CGH). The opto-mechanical design approach addressed the need to have adjustable and highly repeatable interfaces to allow for the complex alignment between the optical sub-assemblies. The alignment techniques employed when mounting the mirrors and throughout instrument integration and end-to-end testing are discussed. Also presented are spatial resolution measurements of the end-to-end point-spread-function that were obtained during testing in the X-ray Cryogenic Facility (XRCF) at NASA Marshall Space Flight Center. Lastly, unresolved issues and off-nominal performance are discussed

ViennaRNA Package 2.0

<p>Abstract</p> <p>Background</p> <p>Secondary structure forms an important intermediate level of description of nucleic acids that encapsulates the dominating part of the folding energy, is often well conserved in evolution, and is routinely used as a basis to explain experimental findings. Based on carefully measured thermodynamic parameters, exact dynamic programming algorithms can be used to compute ground states, base pairing probabilities, as well as thermodynamic properties.</p> <p>Results</p> <p>The <monospace>ViennaRNA</monospace> Package has been a widely used compilation of RNA secondary structure related computer programs for nearly two decades. Major changes in the structure of the standard energy model, the <it>Turner 2004 </it>parameters, the pervasive use of multi-core CPUs, and an increasing number of algorithmic variants prompted a major technical overhaul of both the underlying <monospace>RNAlib</monospace> and the interactive user programs. New features include an expanded repertoire of tools to assess RNA-RNA interactions and restricted ensembles of structures, additional output information such as <it>centroid </it>structures and <it>maximum expected accuracy </it>structures derived from base pairing probabilities, or <it>z</it>-<it>scores </it>for locally stable secondary structures, and support for input in <monospace>fasta</monospace> format. Updates were implemented without compromising the computational efficiency of the core algorithms and ensuring compatibility with earlier versions.</p> <p>Conclusions</p> <p>The <monospace>ViennaRNA Package 2.0</monospace>, supporting concurrent computations <monospace>via OpenMP</monospace>, can be downloaded from <url>http://www.tbi.univie.ac.at/RNA</url>.</p