We describe MUSCLE, a new computer program for creating multiple alignments of protein sequences. Elements of the algorithm include fast distance estimation using kmer counting, progressive alignment using a new profile function we call the logexpectation score, and refinement using treedependent restricted partitioning. The speed and accuracy of MUSCLE are compared with T-Coffee, MAFFT and CLUSTALW on four test sets of reference alignments: BAliBASE, SABmark, SMART and a new benchmark, PREFAB. MUSCLE achieves the highest, or joint highest, rank in accuracy on each of these sets. Without refinement, MUSCLE achieves average accuracy statistically indistinguishable from T-Coffee and MAFFT, and is the fastest of the tested methods for large numbers of sequences, aligning 5000 sequences of average length 350 in 7 min on a current desktop computer. The MUSCLE program, source code and PREFAB test data are freely available at http://www.drive5. com/muscle.

MUSCLE: multiple sequence alignment with high accuracy and high throughput

The design, implementation, and capabilities of an extensible visualization system, UCSF Chimera, are discussed. Chimera is segmented into a core that provides basic services and visualization, and extensions that provide most higher level functionality. This architecture ensures that the extension mechanism satisfies the demands of outside developers who wish to incorporate new features. Two unusual extensions are presented: Multiscale, which adds the ability to visualize large-scale molecular assemblies such as viral coats, and Collaboratory, which allows researchers to share a Chimera session interactively despite being at separate locales. Other extensions include Multalign Viewer, for showing multiple sequence alignments and associated structures; ViewDock, for screening docked ligand orientations; Movie, for replaying molecular dynamics trajectories; and Volume Viewer, for display and analysis of volumetric data. A discussion of the usage of Chimera in real-world situations is given, along with anticipated future directions. Chimera includes full user documentation, is free to academic and nonprofit users, and is available for Microsoft Windows, Linux, Apple Mac OS X, SGI IRIX, and HP Tru64 Unix from http://www.cgl.ucsf.edu/chimera/.

/pdf/ucsf-chimera-a-visualization-system-for-exploratory-research-59xu54fhxg.pdf

UCSF Chimera--a visualization system for exploratory research and analysis.

The Protein Data Bank (PDB; http://www.rcsb.org/pdb/ ) is the single worldwide archive of structural data of biological macromolecules. This paper describes the goals of the PDB, the systems in place for data deposition and access, how to obtain further information, and near-term plans for the future development of the resource.

/pdf/the-protein-data-bank-4lbxxcio6v.pdf

The Protein Data Bank

CCP4mg is a project that aims to provide a general-purpose tool for structural biologists, providing tools for X-ray structure solution, structure comparison and analysis, and publication-quality graphics. The map-fitting tools are available as a stand-alone package, distributed as `Coot'.

/pdf/coot-model-building-tools-for-molecular-graphics-3xns4git70.pdf

Coot: model-building tools for molecular graphics.

抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Motivation: Crystallographers were motivated 10 years ago to develop a simple and consistent data representation for the exchange and archiving of data associated with the crystallographic experiment and the final structure. As this process evolved (and the data grew at near exponential rates) came the recognition that this representation should also facilitate the automated management of the data and, with the aid of additional software for verification and validation, provide improved consistency and accuracy and hence improved scientific inquiry. This realization led to a new Dictionary Definition Language (DDL) and an extensive dictionary based on this DDL for describing macromolecular structure. In broad terms this could be considered an ontology. An important feature in the development of the ontology was the endorsement and ongoing maintenance and support of the International Union of Crystallography (IUCr). While the description of macromolecular structure and the x-ray crystallographic experiment used to derive it represent explicit data, the ontology is extensible and applicable to other less wellcharacterized data domains. Results: Details of the DDL, the dictionaries that have been developed, and software for reading and using this ontology are presented. Availability: Extensive documentation, software tools and the DDL and dictionaries are available from http:// ndbserver.rutgers.edu/ mmcif and associated mirror sites.

/pdf/star-mmcif-an-ontology-for-macromolecular-structure-1nz4nhkbar.pdf

STAR/mmCIF: An ontology for macromolecular structure

Posters are a key component of communicating your science and an important element in a successful scientific career. Posters, while delivering the same high-quality science, offer a different medium from either oral presentations [1] or published papers [2], and should be treated accordingly. Posters should be considered a snapshot of your work intended to engage colleagues in a dialog about the work, or, if you are not present, to be a summary that will encourage the reader to want to learn more. Many a lifelong collaboration [3] has begun in front of a poster board. Here are ten simple rules for maximizing the return on the time-consuming process of preparing and presenting an effective poster.

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Ten Simple Rules for a Good Poster Presentation

Philip E. Bourne*1, Helen M. Berman2, Brian McMahon3, Keith D. Watenpaugh4, John D. Westbrook2 and Paula M.D. Fitzgerald5 * To whom correspondence should be addressed. 1 San Diego Supercomputer Center 4 Physical and Analytical Chemistry 10100 Johns Hopkins Drive Pharmacia and Upjohn La Jolla San Diego CA 92037 USA 7255-209-102 & Department of Pharmacology 301 Henrietta Street University of California San Diego Kalamazoo MI 49001 USA San Diego CA 92093 USA 2 Department of Chemistry 5 Merck Research Laboratories Rutgers University PO Box 2000 Ry50-105 PO Box 939 Rahway NJ 07065 USA Piscataway NJ 08855 USA 3 The International Union of Crystallography 5 Abbey Square Chester CH1 2HU UK

/pdf/the-macromolecular-crystallographic-information-file-mmcif-5et8fkp7bf.pdf

The Macromolecular Crystallographic Information File (mmCIF)

Comparisons of protein sequence via cyclic training of Hidden Markov Models (HMMs) in conjunction with alignments of three-dimensional structure, using the Combinatorial Extension (CE) algorithm, reveal two putative EF-hand metal binding domains in acetylcholinesterase. Based on sequence similarity, putative EF-hands are also predicted for the neuroligin family of cell surface proteins. These predictions are supported by experimental evidence. In the acetylcholinesterase crystal structure from Torpedo californica, the first putative EF-hand region binds the Zn2+ found in the heavy metal replacement structure. Further, the interaction of neuroligin 1 with its cognate receptor neurexin depends on Ca2+. Thus, members of the alpha,beta hydrolase fold family of proteins contain potential Ca2+ binding sites, which in some family members may be critical for heterologous cell associations.

Common EF-hand motifs in cholinesterases and neuroligins suggest a role for Ca2+ binding in cell surface associations.

Citation: Bourne PE, Brenner SE, Eisen MB (2005) PLoS Computational Biology: A new community journal. PLoS Comput Biol 1(1): e4.

/pdf/plos-computational-biology-a-new-community-journal-458rxhwxcz.pdf

Philip E. Bourne

Papers

STAR/mmCIF: An ontology for macromolecular structure

Ten Simple Rules for a Good Poster Presentation

The Macromolecular Crystallographic Information File (mmCIF)

Common EF-hand motifs in cholinesterases and neuroligins suggest a role for Ca2+ binding in cell surface associations.

PLoS Computational Biology: a new community journal.