An Introduction to Programming for Bioscientists: A Python-based Primer

Computing has revolutionized the biological sciences over the past several decades, such that virtually all contemporary research in the biosciences utilizes computer programs. The computational advances have come on many fronts, spurred by fundamental developments in hardware, software, and algorithms. These advances have influenced, and even engendered, a phenomenal array of bioscience fields, including molecular evolution and bioinformatics; genome-, proteome-, transcriptome- and metabolome-wide experimental studies; structural genomics; and atomistic simulations of cellular-scale molecular assemblies as large as ribosomes and intact viruses. In short, much of post-genomic biology is increasingly becoming a form of computational biology. The ability to design and write computer programs is among the most indispensable skills that a modern researcher can cultivate. Python has become a popular programming language in the biosciences, largely because (i) its straightforward semantics and clean syntax make it a readily accessible first language; (ii) it is expressive and well-suited to object-oriented programming, as well as other modern paradigms; and (iii) the many available libraries and third-party toolkits extend the functionality of the core language into virtually every biological domain (sequence and structure analyses, phylogenomics, workflow management systems, etc.). This primer offers a basic introduction to coding, via Python, and it includes concrete examples and exercises to illustrate the language's usage and capabilities; the main text culminates with a final project in structural bioinformatics. A suite of Supplemental Chapters is also provided. Starting with basic concepts, such as that of a 'variable', the Chapters methodically advance the reader to the point of writing a graphical user interface to compute the Hamming distance between two DNA sequences.Comment: 65 pages total, including 45 pages text, 3 figures, 4 tables, numerous exercises, and 19 pages of Supporting Information; currently in press at PLOS Computational Biolog

Claws, Disorder, and Conformational Dynamics of the C Terminal Region of Human Desmoplakin

Multicellular organisms consist of cells that interact via elaborate adhesion complexes. Desmosomes are membrane-associated adhesion complexes that mechanically tether the cytoskeletal intermediate filaments (IFs) between two adjacent cells, creating a network of tough connections in tissues such as skin and heart. Desmoplakin (DP) is the key desmosomal protein that binds IFs, and the DP·IF association poses a quandary: desmoplakin must stably and tightly bind IFs to maintain the structural integrity of the desmosome. Yet, newly synthesized DP must traffic along the cytoskeleton to the site of nascent desmosome assembly without “sticking” to the IF network, implying weak or transient DP···IF contacts. Recent work reveals that these contacts are modulated by post-translational modifications (PTMs) in DP’s C-terminal tail (DP_CTT). Using molecular dynamics simulations, we have elucidated the structural basis of these PTM-induced effects. Our simulations, nearing 2 μs in aggregate, indicate that phosphorylation of S2849 induces an “arginine claw” in desmoplakin’s C-terminal tail. If a key arginine, R2834, is methylated, the DP_CTT preferentially samples conformations that are geometrically well-suited as substrates for processive phosphorylation by the cognate kinase GSK3. We suggest that DP_CTT is a molecular switch that modulates, via its conformational dynamics, DP’s overall efficacy as a substrate for GSK3. Finally, we show that the fluctuating DP_CTT can contact other parts of DP, suggesting a competitive binding mechanism for the modulation of DP···IF interactions

Toward a Designable Extracellular Matrix: Molecular Dynamics Simulations of an Engineered Laminin-mimetic, Elastin-like Fusion Protein

Native extracellular matrices (ECMs), such as those of the human brain and other neural tissues, exhibit networks of molecular interactions between specific matrix proteins and other tissue components. Guided by these naturally self-assembling supramolecular systems, we have designed a matrix-derived protein chimera that contains a laminin globular-like (LG) domain fused to an elastin-like polypeptide (ELP). All-atom, classical molecular dynamics simulations of our designed laminin-elastin fusion protein reveal temperature-dependent conformational changes, in terms of secondary structure composition, solvent accessible surface area, hydrogen bonding, and surface hydration. These properties illuminate the phase behavior of this fusion protein, via the emergence of $\beta$-sheet character in physiologically-relevant temperature ranges.Comment: 53 pages, 7 figures in the main text; Supporting Information contains 1 table, 12 figures, 4 trajectory animations (videos

Nothing Lasts Forever: Environmental Discourses on the Collapse of Past Societies

The study of the collapse of past societies raises many questions for the theory and practice of archaeology. Interest in collapse extends as well into the natural sciences and environmental and sustainability policy. Despite a range of approaches to collapse, the predominant paradigm is environmental collapse, which I argue obscures recognition of the dynamic role of social processes that lie at the heart of human communities. These environmental discourses, together with confusion over terminology and the concepts of collapse, have created widespread aporia about collapse and resulted in the creation of mixed messages about complex historical and social processes

Sample flowchart for a sorting algorithm.

<p>This flowchart illustrates the conditional constructs, loops, and other elements of control flow that comprise an algorithm for sorting, from smallest to largest, an arbitrary list of numbers (the algorithm is known as “bubble sort”). In this type of diagram, arrows symbolize the flow of logic (control flow), rounded rectangles mark the start and end points, slanted parallelograms indicate I/O (e.g., a user-provided list), rectangles indicate specific subroutines or procedures (blocks of statements), and diamonds denote conditional constructs (branch points). Note that this sorting algorithm involves a pair of nested loops over the list size (blue and orange), meaning that the calculation cost will go as the square of the input size (here, an <i>N</i>-element list); this cost can be halved by adjusting the inner loop conditional to be “”, as the largest <i>i</i> elements will have already reached their final positions.</p

Overview of the Supplemental Chapters (S1 Text).

<p>Overview of the Supplemental Chapters (<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004867#pcbi.1004867.s001" target="_blank">S1 Text</a>).</p

Common mathematical operators in Python.

<p>Common mathematical operators in Python.</p