Matt: Local Flexibility Aids Protein Multiple Structure Alignment

Even when there is agreement on what measure a protein multiple structure alignment should be optimizing, finding the optimal alignment is computationally prohibitive. One approach used by many previous methods is aligned fragment pair chaining, where short structural fragments from all the proteins are aligned against each other optimally, and the final alignment chains these together in geometrically consistent ways. Ye and Godzik have recently suggested that adding geometric flexibility may help better model protein structures in a variety of contexts. We introduce the program Matt (Multiple Alignment with Translations and Twists), an aligned fragment pair chaining algorithm that, in intermediate steps, allows local flexibility between fragments: small translations and rotations are temporarily allowed to bring sets of aligned fragments closer, even if they are physically impossible under rigid body transformations. After a dynamic programming assembly guided by these “bent” alignments, geometric consistency is restored in the final step before the alignment is output. Matt is tested against other recent multiple protein structure alignment programs on the popular Homstrad and SABmark benchmark datasets. Matt's global performance is competitive with the other programs on Homstrad, but outperforms the other programs on SABmark, a benchmark of multiple structure alignments of proteins with more distant homology. On both datasets, Matt demonstrates an ability to better align the ends of α-helices and β-strands, an important characteristic of any structure alignment program intended to help construct a structural template library for threading approaches to the inverse protein-folding problem. The related question of whether Matt alignments can be used to distinguish distantly homologous structure pairs from pairs of proteins that are not homologous is also considered. For this purpose, a p-value score based on the length of the common core and average root mean squared deviation (RMSD) of Matt alignments is shown to largely separate decoys from homologous protein structures in the SABmark benchmark dataset. We postulate that Matt's strong performance comes from its ability to model proteins in different conformational states and, perhaps even more important, its ability to model backbone distortions in more distantly related proteins

Computational approaches to modeling the conserved structural core among distantly homologous proteins

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009.Cataloged from PDF version of thesis.Includes bibliographical references (p. 95-103).Modem techniques in biology have produced sequence data for huge quantities of proteins, and 3-D structural information for a much smaller number of proteins. We introduce several algorithms that make use of the limited available structural information to classify and annotate proteins with structures that are unknown, but similar to solved structures. The first algorithm is actually a tool for better understanding solved structures themselves. Namely, we introduce the multiple alignment algorithm Matt (Multiple Alignment with Translations and Twists), an aligned fragment pair chaining algorithm that, in intermediate steps, allows local flexibility between fragments. Matt temporarily allows small translations and rotations to bring sets of fragments into closer alignment than physically possible under rigid body transformation. The second algorithm, BetaWrapPro, is designed to recognize sequences of unknown structure that belong to specific all-beta fold classes. BetaWrapPro employs a "wrapping" algorithm that uses long-distance pairwise residue preferences to recognize sequences belonging to the beta-helix and the beta-trefoil classes. It uses hand-curated beta-strand templates based on solved structures. Finally, SMURF (Structural Motifs Using Random Fields) combines ideas from both these algorithms into a general method to recognize beta-structural motifs using both sequence information and long-distance pairwise correlations involved in beta-sheet formation. For any beta-structural fold, SMURF uses Matt to automatically construct a template from an alignment of solved 3-D structures.(cont.) From this template, SMURF constructs a Markov random field that combines a profile hidden Markov model together with pairwise residue preferences of the type introduced by BetaWrapPro. The efficacy of SMURF is demonstrated on three beta-propeller fold classes.by Matthew Ewald Menke.Ph.D

Predicting the beta-trefoil fold from protein sequence data

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2004.Includes bibliographical references (p. 45-47).A method is presented that uses [beta]-strand interactions at both the sequence and the atomic level, to predict the beta-structural motifs in protein sequences. A program called Wrap-and-Pack implements this method, and is shown to recognize β-trefoils, an important class of globular β-structures, in the Protein Data Bank with 92% specificity and 92.3% sensitivity in cross-validation. It is demonstrated that Wrap-and-Pack learns each of the ten known SCOP β-trefoil families, when trained primarily on β-structures that are not β-trefoils, together with 3D structures of known β-trefoils from outside the family. Wrap-and-Pack also predicts many proteins of unknown structure to be β-trefoils. The computational method used here may generalize to other β-structures for which strand topology and profiles of residue accessibility are well conserved.by Matthew Ewald Menke.S.M

BETASCAN: Probable β\beta-amyloids Identified by Pairwise Probabilistic Analysis

Amyloids and prion proteins are clinically and biologically important $\beta$-structures, whose supersecondary structures are difficult to determine by standard experimental or computational means. In addition, significant conformational heterogeneity is known or suspected to exist in many amyloid fibrils. Recent work has indicated the utility of pairwise probabilistic statistics in $\beta$-structure prediction. We develop here a new strategy for $\beta$-structure prediction, emphasizing the determination of $\beta$-strands and pairs of $\beta$-strands as fundamental units of $\beta$-structure. Our program, BETASCAN, calculates likelihood scores for potential $\beta$-strands and strand-pairs based on correlations observed in parallel $\beta$-sheets. The program then determines the strands and pairs with the greatest local likelihood for all of the sequence's potential $\beta$-structures. BETASCAN suggests multiple alternate folding patterns and assigns relative a priori probabilities based solely on amino acid sequence, probability tables, and pre-chosen parameters. The algorithm compares favorably with the results of previous algorithms (BETAPRO, PASTA, SALSA, TANGO, and Zyggregator) in $\beta$-structure prediction and amyloid propensity prediction. Accurate prediction is demonstrated for experimentally determined amyloid $\beta$-structures, for a set of known $\beta$-aggregates, and for the parallel $\beta$-strands of $\beta$-helices, amyloid-like globular proteins. BETASCAN is able both to detect $\beta$-strands with higher sensitivity and to detect the edges of $\beta$-strands in a richly $\beta$-like sequence. For two proteins (A$\beta$ and Het-s), there exist multiple sets of experimental data implying contradictory structures; BETASCAN is able to detect each competing structure as a potential structure variant. The ability to correlate multiple alternate $\beta$-structures to experiment opens the possibility of computational investigation of prion strains and structural heterogeneity of amyloid. BETASCAN is publicly accessible on the Web at http://betascan.csail.mit.edu

Time-resolved synchrotron X-ray micro-tomography datasets of drainage and imbibition in carbonate rocks

Multiphase flow in permeable media is a complex pore-scale phenomenon, which is important in many natural and industrial processes. To understand the pore-scale dynamics of multiphase flow, we acquired time-series synchrotron X-ray micro-tomographic data at a voxel-resolution of 3.28 μm and time-resolution of 38 s during drainage and imbibition in a carbonate rock, under a capillary-dominated flow regime at elevated pressure. The time-series data library contains 496 tomographic images (gray-scale and segmented) for the complete drainage process, and 416 tomographic images (gray-scale and segmented) for the complete imbibition process. These datasets have been uploaded on the publicly accessible British Geological Survey repository, with the objective that the time-series information can be used by other groups to validate pore-scale displacement models such as direct simulations, pore-network and neural network models, as well as to investigate flow mechanisms related to the displacement and trapping of the non-wetting phase in the pore space. These datasets can also be used for improving segmentation algorithms for tomographic data with limited projections

Isolation of networking process in a browser

Computer programs and applications are often designed such that sub-tasks of a program are executed by a separate process spawned by the main program or application. An advantage to such a design is resilience, e.g., even if one process fails, the remaining processes continue execution, even as the failed process is started anew. In the context of web browser applications, networking requests are typically not spawned as separate processes but rather handled by the main browser process itself. This can lead to problems of stability, security, and resilience. The techniques of this disclosure spawn the networking tasks of a web browser into a separate process, and can provide improved stability, security, and resilience

STITCHER: Dynamic assembly of likely amyloid and prion β-structures from secondary structure predictions

The supersecondary structure of amyloids and prions, proteins of intense clinical and biological interest, are difficult to determine by standard experimental or computational means. In addition, significant conformational heterogeneity is known or suspected to exist in many amyloid fibrils. Previous work has demonstrated that probability-based prediction of discrete β-strand pairs can offer insight into these structures. Here, we devise a system of energetic rules that can be used to dynamically assemble these discrete β-strand pairs into complete amyloid β-structures. The STITCHER algorithm progressively ‘stitches’ strand-pairs into full β-sheets based on a novel free-energy model, incorporating experimentally observed amino-acid side-chain stacking contributions, entropic estimates, and steric restrictions for amyloidal parallel β-sheet construction. A dynamic program computes the top 50 structures and returns both the highest scoring structure and a consensus structure taken by polling this list for common discrete elements. Putative structural heterogeneity can be inferred from sequence regions that compose poorly. Predictions show agreement with experimental models of Alzheimer's amyloid beta peptide and the Podospora anserina Het-s prion. Predictions of the HET-s homolog HET-S also reflect experimental observations of poor amyloid formation. We put forward predicted structures for the yeast prion Sup35, suggesting N-terminal structural stability enabled by tyrosine ladders, and C-terminal heterogeneity. Predictions for the Rnq1 prion and alpha-synuclein are also given, identifying a similar mix of homogenous and heterogeneous secondary structure elements. STITCHER provides novel insight into the energetic basis of amyloid structure, provides accurate structure predictions, and can help guide future experimental studies. Proteins 2011

Discovery of the 2010 Eruption and the Pre-Eruption Light Curve for Recurrent Nova U Scorpii

We report the discovery by B. G. Harris and S. Dvorak on JD 2455224.9385 (2010 Jan 28.4385 UT) of the predicted eruption of the recurrent nova U Scorpii (U Sco). We also report on 815 magnitudes (and 16 useful limits) on the pre-eruption light curve in the UBVRI and Sloan r' and i' bands from 2000.4 up to 9 hours before the peak of the January 2010 eruption. We found no significant long-term variations, though we did find frequent fast variations (flickering) with amplitudes up to 0.4 mag. We show that U Sco did not have any rises or dips with amplitude greater than 0.2 mag on timescales from one day to one year before the eruption. We find that the peak of this eruption occurred at JD 2455224.69+-0.07 and the start of the rise was at JD 2455224.32+-0.12. From our analysis of the average B-band flux between eruptions, we find that the total mass accreted between eruptions is consistent with being a constant, in agreement with a strong prediction of nova trigger theory. The date of the next eruption can be anticipated with an accuracy of +-5 months by following the average B-band magnitudes for the next ~10 years, although at this time we can only predict that the next eruption will be in the year 2020+-2.Comment: Astronomical Journal submitted, 36 pages, 3 figures, full table

Order enables efficient electron-hole separation at an organic heterojunction with a small energy loss.

Donor-acceptor organic solar cells often show low open-circuit voltages (V OC) relative to their optical energy gap (E g) that limit power conversion efficiencies to ~12%. This energy loss is partly attributed to the offset between E g and that of intermolecular charge transfer (CT) states at the donor-acceptor interface. Here we study charge generation occurring in PIPCP:PC61BM, a system with a very low driving energy for initial charge separation (E g-E CT ~ 50 meV) and a high internal quantum efficiency (η IQE ~ 80%). We track the strength of the electric field generated between the separating electron-hole pair by following the transient electroabsorption optical response, and find that while localised CT states are formed rapidly (<100 fs) after photoexcitation, free charges are not generated until 5 ps after photogeneration. In PIPCP:PC61BM, electronic disorder is low (Urbach energy <27 meV) and we consider that free charge separation is able to outcompete trap-assisted non-radiative recombination of the CT state

Shared imaging markers of fatigue across multiple sclerosis, aquaporin-4 antibody neuromyelitis optica spectrum disorder and MOG antibody disease

Fatigue is frequently reported by patients with multiple sclerosis, aquaporin-4-antibody neuromyelitis optica spectrum disorder and myelin-oligodendrocyte-glycoprotein antibody disease; thus they could share a similar pathophysiological mechanism. In this cross-sectional cohort study, we assessed the association of fatigue with resting-state functional MRI, diffusion and structural imaging measures across these three disorders. Sixteen patients with multiple sclerosis, 17 with aquaporin-4-antibody neuromyelitis optica spectrum disorder and 17 with myelin-oligodendrocyte-glycoprotein antibody disease assessed, outside of relapses, at the Oxford Neuromyelitis Optica Service underwent Modified Fatigue Impact Scale, Hospital Anxiety and Depression Scale and Expanded Disability Status Scale scoring. A 3T brain and spinal cord MRI was used to derive cortical, deep grey and white matter volumetrics, lesions volume, fractional anisotropy, brain functional connectivity metrics, cervical spinal cord cross-sectional area, spinal cord magnetic transfer ratio and average functional connectivity between the ventral and the dorsal horns of the cervical cord. Linear relationships between MRI measures and total-, cognitive- and physical-fatigue scores were assessed. All analyses were adjusted for correlated clinical regressors. No significant differences in baseline clinical characteristics, fatigue, depression and anxiety questionnaires and disability measures were seen across the three diseases, except for older age in patients with aquaporin-4-antibody neuromyelitis optica spectrum disorder (P = 0.0005). In the total cohort, median total-fatigue score was 35.5 (range 3-72), and 42% of patients were clinically fatigued. A positive correlation existed between the total-fatigue score and functional connectivity of the executive/fronto-temporal network in the in left middle temporal gyrus (P = 0.033) and between the physical-fatigue score and functional connectivity of the sensory-motor network (P = 0.032) in both pre- and post-central gyri. A negative relationship was found between the total-fatigue score and functional connectivity of the salience network (P = 0.023) and of the left fronto-parietal network (P = 0.026) in the right supramarginal gyrus and left superior parietal lobe. No clear relationship between fatigue subscores and the average functional connectivity of the spinal cord was found. Cognitive-fatigue scores were positively associated with white matter lesion volume (P = 0.018) and negatively associated with white matter fractional anisotropy (P = 0.032). Structural, diffusion and functional connectivity alterations were not influenced by the disease group. Functional and structural imaging metrics associated with fatigue relate to brain rather than spinal cord abnormalities. Salience and sensory-motor networks alterations in relation to fatigue might indicate a disconnection between the perception of the interior body state and activity and the actual behavioural responses and performances (reversible or irreversible). Future research should focus on functional rehabilitative strategies