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/.

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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'.

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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

Scientists spend their lives analyzing data by the systematic study of the structure and behavior of the physical and natural world using both observation and experiment—objective analysis. But when it comes to decision-making, scientists are also humans with accompanying subjectivity. Put colloquially, we have both heart and head—and are capable of being simultaneously subjective and objective. Here we posit that bringing more objectivity (\"head\") to decisions is a good thing. It’s a key part of \"critical thinking,\" the \"Socratic questioning\" method. We are not suggesting, that like Mr. Spock, we should be driven entirely by rationality, nor are we considering the merits of various reasoning systems [1]; we are simply examining why greater objectivity helps in providing a simple way to achieve improved objectivity. So, to start, is objectivity indeed better than subjectivity? To address this question, it’s useful to look at the 2 opposite ends of the spectrum: objectivity is really the application of pure logic (something is either right or wrong, more or less, etc.), whereas subjectivity [2] is embodied in the form of what is often called Cartesian Doubt or skepticism (that the knowledge of anything outside ones direct experience has to be considered as unsure). In certain cases, increased objectivity is superior, for example, when the decision being taken leads toward a measurable or quantifiable outcome: if there is a specific goal in mind, then it’s very useful to be able to estimate how close that decision might get you to that goal before you set out on the path. In real life, most decisions are a mixture of head and heart, but with these rules, we hope to increase both the accuracy and quantity of the head part while not neglecting the heart. But enough of the epistemological concepts, what we want is to make better decisions (better here being more objective) and look at 10 ways in which we might do this, culminating in a simple tool that anyone with a spreadsheet (or even a pen and paper) can use. Each rule is accompanied by a use case, some drawn from 2 previous Ten simple rules: Ten simple rules for graduate students [3] and Ten simple rules for selecting a postdoctoral position [4]. We will culminate with a worked example that illustrates this approach. Every lab needs a good coffee machine, and we are inspired by the example of the famous Trojan Room coffee pot. Based in the old computer laboratory of the University of Cambridge, England, in 1991, it provided the inspiration for the world’s first webcam [5]. So here we show how to make sure your coffee is well up to par! PLOS COMPUTATIONAL BIOLOGY

Ten simple rules for more objective decision-making.

PDBiib is an extensible object oriented class library written in C++ for representing the 3-dimensional structure of biological macromolecules. PDBlib forms the kernel of a larger software framework being developed for assiting in knowledge discovery from macromolecular structure data. The software design strategy used by PDBlib, how the library may be used and several prototype applications that use the library are summarized. PDBlib represents the structural features of proteins, DNA, RNA, and complexes thereof, at a level of detail on a par with that which can be parsed from a Protein Data Bank (PDB) entry. However, the memory resident representation of the macromolecule is independent of the PDB entry and can be obtained from other back-end data sources, for example, e.xJsting relational databases and our own object oriented database (OOPDB) built on top of the commercial object oriented database, ObjectStore. At the front-end are several prototype applications thal use the library: Macromolecular Query Language (MMQL) is based a separate class library (MMQLlib) for building complex queries pertaining to macromolecular structure; PDBtool is an interactive structure verification tool; and PDBview, is a structure rendering tool used either as a standalone tool or as part of another application. Each of these software components are described. All software is available via anonymous ftp from cuhhca.hhmi, columbia, edu i

/pdf/design-and-application-of-a-c-macromolecular-class-library-qvqj8pixu7.pdf

Design and application of a C++ macromolecular class library.

The format of communicating scientific, technical, and medical (STM)11 information through professional journals has changed relatively little since the publication in 1665 of the Philosophical Transactions of the Royal Society , the world's first journal devoted exclusively to science. Although advances in information technology have dramatically altered the search and discovery of scientific information, other aspects—such as migrating from paper to electronic publishing, moving from a “static” to a “living” document, or exploiting social media tools to disseminate STM information—have been slow in coming. The transformations seen in the popular press to better present and relay complex information have undoubtedly raised readers' expectations of the scientific-publishing community about how to find and use information. In this Q&A article, 5 experts—a librarian, a publisher, a technology expert, and 2 editors representing traditional and new-concept journals—discuss their views on the communication of scientific information.

Why do you think scientific journals, in general, have not taken advantage of technology to the same extent as the lay press? 

Michael A. Keller: Actually, scientific journals were early innovators in e-publishing, developing and using features and functions useful in some cases beyond the academic sphere. While I suppose that the assertion of lagging adoption or de novo development of new features by scientific journals with particular regard to social networking functions could be supported in some measure, one rejoinder might be to question whether such functions were pertinent to STM literature. It might also be the case that having been early innovators in the first decade or so of e-publishing, scientific journals have been on a sort of plateau of development recently, which state is about to change as STM journal publishers are starting to explore new possibilities in data archiving and sharing, imaging technologies permitting much higher resolution of views, and advanced modes of …

/pdf/communication-of-scientific-information-is-it-time-to-17s8oupjzv.pdf

Communication of Scientific Information: Is It Time to Reassess?

Overview We suspect that there is a level of granularity of protein structure intermediate between the classical levels of ‘architecture’ and ‘topology’, as reflected in such phenomena as extensive 3D structural similarity above the level of (super)folds. Here, we examine this notion of architectural identity despite topological variability, starting with a concept that we call the ‘Urfold’. We believe that this model could offer a new conceptual approach for protein structural analysis and classification: indeed, the Urfold concept may help reconcile various phenomena that have been frequently recognized or debated for years, such as the precise meaning of ‘significant’ structural overlap and the degree of continuity of fold space. More broadly, the role of structural similarity in sequence/structure/function evolution has been studied via many models over the years; the Urfold may help synthesize these models into a generalized, consistent framework, by addressing a conceptual gap that we believe exists between the architecture and topology levels of structural classification schemes.

https://www.biorxiv.org/content/biorxiv/early/2019/08/07/728030.full.pdf

Philip E. Bourne

Papers

Ten simple rules for more objective decision-making.

Design and application of a C++ macromolecular class library.

Communication of Scientific Information: Is It Time to Reassess?

The Urfold: Structural Similarity Just above the Superfold Level?

Protein-nucleic acid interactions. Folding and binding.