ThYme: a database for thioester-active enzymes

The ThYme (Thioester-active enzYme; http://www.enzyme.cbirc.iastate.edu) database has been constructed to bring together amino acid sequences and 3D (tertiary) structures of all the enzymes constituting the fatty acid synthesis and polyketide synthesis cycles. These enzymes are active on thioester-containing substrates, specifically those that are parts of the acyl-CoA synthase, acyl-CoA carboxylase, acyl transferase, ketoacyl synthase, ketoacyl reductase, hydroxyacyl dehydratase, enoyl reductase and thioesterase enzyme groups. These groups have been classified into families, members of which are similar in sequences, tertiary structures and catalytic mechanisms, implying common protein ancestry. ThYme is continually updated as sequences and tertiary structures become available

Multiple structure alignment and consensus identification for proteins

<p>Abstract</p> <p>Background</p> <p>An algorithm is presented to compute a multiple structure alignment for a set of proteins and to generate a consensus (pseudo) protein which captures common substructures present in the given proteins. The algorithm represents each protein as a sequence of triples of coordinates of the alpha-carbon atoms along the backbone. It then computes iteratively a sequence of transformation matrices (i.e., translations and rotations) to align the proteins in space and generate the consensus. The algorithm is a heuristic in that it computes an approximation to the optimal alignment that minimizes the sum of the pairwise distances between the consensus and the transformed proteins.</p> <p>Results</p> <p>Experimental results show that the algorithm converges quite rapidly and generates consensus structures that are visually similar to the input proteins. A comparison with other coordinate-based alignment algorithms (MAMMOTH and MATT) shows that the proposed algorithm is competitive in terms of speed and the sizes of the conserved regions discovered in an extensive benchmark dataset derived from the HOMSTRAD and SABmark databases.</p> <p>The algorithm has been implemented in C++ and can be downloaded from the project's web page. Alternatively, the algorithm can be used via a web server which makes it possible to align protein structures by uploading files from local disk or by downloading protein data from the RCSB Protein Data Bank.</p> <p>Conclusions</p> <p>An algorithm is presented to compute a multiple structure alignment for a set of proteins, together with their consensus structure. Experimental results show its effectiveness in terms of the quality of the alignment and computational cost.</p

Towards Reliable Automatic Protein Structure Alignment

A variety of methods have been proposed for structure similarity calculation, which are called structure alignment or superposition. One major shortcoming in current structure alignment algorithms is in their inherent design, which is based on local structure similarity. In this work, we propose a method to incorporate global information in obtaining optimal alignments and superpositions. Our method, when applied to optimizing the TM-score and the GDT score, produces significantly better results than current state-of-the-art protein structure alignment tools. Specifically, if the highest TM-score found by TMalign is lower than (0.6) and the highest TM-score found by one of the tested methods is higher than (0.5), there is a probability of (42%) that TMalign failed to find TM-scores higher than (0.5), while the same probability is reduced to (2%) if our method is used. This could significantly improve the accuracy of fold detection if the cutoff TM-score of (0.5) is used. In addition, existing structure alignment algorithms focus on structure similarity alone and simply ignore other important similarities, such as sequence similarity. Our approach has the capacity to incorporate multiple similarities into the scoring function. Results show that sequence similarity aids in finding high quality protein structure alignments that are more consistent with eye-examined alignments in HOMSTRAD. Even when structure similarity itself fails to find alignments with any consistency with eye-examined alignments, our method remains capable of finding alignments highly similar to, or even identical to, eye-examined alignments.Comment: Peer-reviewed and presented as part of the 13th Workshop on Algorithms in Bioinformatics (WABI2013

SMAP-WS: a parallel web service for structural proteome-wide ligand-binding site comparison

The proteome-wide characterization and analysis of protein ligand-binding sites and their interactions with ligands can provide pivotal information in understanding the structure, function and evolution of proteins and for designing safe and efficient therapeutics. The SMAP web service (SMAP-WS) meets this need through parallel computations designed for 3D ligand-binding site comparison and similarity searching on a structural proteome scale. SMAP-WS implements a shape descriptor (the Geometric Potential) that characterizes both local and global topological properties of the protein structure and which can be used to predict the likely ligand-binding pocket [Xie,L. and Bourne,P.E. (2007) A robust and efficient algorithm for the shape description of protein structures and its application in predicting ligand-binding sites. BMC bioinformatics, 8 (Suppl. 4.), S9.]. Subsequently a sequence order independent profile–profile alignment (SOIPPA) algorithm is used to detect and align similar pockets thereby finding protein functional and evolutionary relationships across fold space [Xie, L. and Bourne, P.E. (2008) Detecting evolutionary relationships across existing fold space, using sequence order-independent profile-profile alignments. Proc. Natl Acad. Sci. USA, 105, 5441–5446]. An extreme value distribution model estimates the statistical significance of the match [Xie, L., Xie, L. and Bourne, P.E. (2009) A unified statistical model to support local sequence order independent similarity searching for ligand-binding sites and its application to genome-based drug discovery. Bioinformatics, 25, i305–i312.]. These algorithms have been extensively benchmarked and shown to outperform most existing algorithms. Moreover, several predictions resulting from SMAP-WS have been validated experimentally. Thus far SMAP-WS has been applied to predict drug side effects, and to repurpose existing drugs for new indications. SMAP-WS provides both a user-friendly web interface and programming API for scientists to address a wide range of compute intense questions in biology and drug discovery

Capacitance of a quantum dot from the channel-anisotropic two-channel Kondo model

We investigate the charge fluctuations of a large quantum dot coupled to a two-dimensional electron gas via a quantum point contact following the work of Matveev. We limit our discussion to the case where exactly two channels enter the dot and we discuss the role of an anisotropy between the transmission coefficients (for these two channels) at the constriction. Experimentally, a channel-anisotropy can be introduced applying a relatively weak in-plane magnetic field to the system when only one ``orbital'' channel is open. The magnetic field leads to different transmission amplitudes for spin-up and spin-down electrons. In a strong magnetic field the anisotropic two-channel limit corresponds to two (spin-polarized) orbital channels entering the dot. The physics of the charge fluctuations can be captured using a mapping on the channel-anisotropic two-channel Kondo model. For the case of weak reflection at the point contact this has already briefly been stressed by one of us in PRB {\bf 64}, 161302R (2001). This mapping is also appropriate to discuss the conductance behavior of a two-contact set-up in strong magnetic field. Here, we elaborate on this approach and also discuss an alternative solution using a mapping on a channel-isotropic Kondo model. In addition we consider the limit of weak transmission. We show that the Coulomb-staircase behavior of the charge in the dot as a function of the gate voltage, is already smeared out by a small channel-anisotropy both in the weak- and strong transmission limits.Comment: 17 pages, 4 figures, 1 Table; Expands cond-mat/0101126; Sec. VI on 2-contact setup added (Final version for PRB

Fr-TM-align: a new protein structural alignment method based on fragment alignments and the TM-score

©2008 Pandit and Skolnick; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. This article is available from: http://www.biomedcentral.com/1471-2105/9/531doi:10.1186/1471-2105-9-531Background: Protein tertiary structure comparisons are employed in various fields of contemporary structural biology. Most structure comparison methods involve generation of an initial seed alignment, which is extended and/or refined to provide the best structural superposition between a pair of protein structures as assessed by a structure comparison metric. One such metric, the TM-score, was recently introduced to provide a combined structure quality measure of the coordinate root mean square deviation between a pair of structures and coverage. Using the TM-score, the TM-align structure alignment algorithm was developed that was often found to have better accuracy and coverage than the most commonly used structural alignment programs; however, there were a number of situations when this was not true. Results: To further improve structure alignment quality, the Fr-TM-align algorithm has been developed where aligned fragment pairs are used to generate the initial seed alignments that are then refined using dynamic programming to maximize the TM-score. For the assessment of the structural alignment quality from Fr-TM-align in comparison to other programs such as CE and TMalign, we examined various alignment quality assessment scores such as PSI and TM-score. The assessment showed that the structural alignment quality from Fr-TM-align is better in comparison to both CE and TM-align. On average, the structural alignments generated using Fr-TM-align have a higher TM-score (~9%) and coverage (~7%) in comparison to those generated by TM-align. Fr- TM-align uses an exhaustive procedure to generate initial seed alignments. Hence, the algorithm is computationally more expensive than TM-align. Conclusion: Fr-TM-align, a new algorithm that employs fragment alignment and assembly provides better structural alignments in comparison to TM-align. The source code and executables of Fr- TM-align are freely downloadable at: http://cssb.biology.gatech.edu/skolnick/files/FrTMalign/

FLORA: a novel method to predict protein function from structure in diverse superfamilies

Predicting protein function from structure remains an active area of interest, particularly for the structural genomics initiatives where a substantial number of structures are initially solved with little or no functional characterisation. Although global structure comparison methods can be used to transfer functional annotations, the relationship between fold and function is complex, particularly in functionally diverse superfamilies that have evolved through different secondary structure embellishments to a common structural core. The majority of prediction algorithms employ local templates built on known or predicted functional residues. Here, we present a novel method (FLORA) that automatically generates structural motifs associated with different functional sub-families (FSGs) within functionally diverse domain superfamilies. Templates are created purely on the basis of their specificity for a given FSG, and the method makes no prior prediction of functional sites, nor assumes specific physico-chemical properties of residues. FLORA is able to accurately discriminate between homologous domains with different functions and substantially outperforms (a 2–3 fold increase in coverage at low error rates) popular structure comparison methods and a leading function prediction method. We benchmark FLORA on a large data set of enzyme superfamilies from all three major protein classes (α, β, αβ) and demonstrate the functional relevance of the motifs it identifies. We also provide novel predictions of enzymatic activity for a large number of structures solved by the Protein Structure Initiative. Overall, we show that FLORA is able to effectively detect functionally similar protein domain structures by purely using patterns of structural conservation of all residues

Strong Interactions of Single Atoms and Photons near a Dielectric Boundary

Modern research in optical physics has achieved quantum control of strong interactions between a single atom and one photon within the setting of cavity quantum electrodynamics (cQED). However, to move beyond current proof-of-principle experiments involving one or two conventional optical cavities to more complex scalable systems that employ N >> 1 microscopic resonators requires the localization of individual atoms on distance scales < 100 nm from a resonator's surface. In this regime an atom can be strongly coupled to a single intracavity photon while at the same time experiencing significant radiative interactions with the dielectric boundaries of the resonator. Here, we report an initial step into this new regime of cQED by way of real-time detection and high-bandwidth feedback to select and monitor single Cesium atoms localized ~100 nm from the surface of a micro-toroidal optical resonator. We employ strong radiative interactions of atom and cavity field to probe atomic motion through the evanescent field of the resonator. Direct temporal and spectral measurements reveal both the significant role of Casimir-Polder attraction and the manifestly quantum nature of the atom-cavity dynamics. Our work sets the stage for trapping atoms near micro- and nano-scopic optical resonators for applications in quantum information science, including the creation of scalable quantum networks composed of many atom-cavity systems that coherently interact via coherent exchanges of single photons.Comment: 8 pages, 5 figures, Supplemental Information included as ancillary fil

The Quantum Internet

Quantum networks offer a unifying set of opportunities and challenges across exciting intellectual and technical frontiers, including for quantum computation, communication, and metrology. The realization of quantum networks composed of many nodes and channels requires new scientific capabilities for the generation and characterization of quantum coherence and entanglement. Fundamental to this endeavor are quantum interconnects that convert quantum states from one physical system to those of another in a reversible fashion. Such quantum connectivity for networks can be achieved by optical interactions of single photons and atoms, thereby enabling entanglement distribution and quantum teleportation between nodes.Comment: 15 pages, 6 figures Higher resolution versions of the figures can be downloaded from the following link: http://www.its.caltech.edu/~hjkimble/QNet-figures-high-resolutio

GPCRDB: information system for G protein-coupled receptors

The GPCRDB is a Molecular Class-Specific Information System (MCSIS) that collects, combines, validates and disseminates large amounts of heterogeneous data on G protein-coupled receptors (GPCRs). The GPCRDB contains experimental data on sequences, ligand-binding constants, mutations and oligomers, as well as many different types of computationally derived data such as multiple sequence alignments and homology models. The GPCRDB provides access to the data via a number of different access methods. It offers visualization and analysis tools, and a number of query systems. The data is updated automatically on a monthly basis. The GPCRDB can be found online at http://www.gpcr.org/7tm/