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 molecular biology, biochemistry, and other 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.

Toward a Designable Extracellular Matrix: Molecular Dynamics Simulations of an Engineered Laminin-Mimetic, Elastin-Like Fusion Protein.

Native extracellular matrices (ECMs) 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). This bipartite design offers a flexible protein engineering platform: (i) laminin is a key multifunctional component of the ECM in human brains and other neural tissues, making it an ideal bioactive component of our fusion, and (ii) ELPs, known to be well-tolerated in vivo, provide a self-assembly scaffold with tunable physicochemical (viscoelastic, thermoresponsive) properties. Experimental characterization of novel proteins is resource-intensive, and examining many conceivable designs would be a formidable challenge in the laboratory. Computational approaches offer a way forward: molecular dynamics (MD) simulations can be used to analyze the structural/physical behavior of candidate LG-ELP fusion proteins, particularly in terms of conformational properties salient to our design goals, such as assembly propensity in a temperature range spanning the inverse temperature transition. As a first step in examining the physical characteristics of a model LG-ELP fusion protein, including its temperature-dependent structural behavior, we simulated the protein over a range of physiologically relevant temperatures (290-320 K). We find that the ELP region, built upon the archetypal (VPGXG)5 scaffold, is quite flexible and has a propensity for ß-rich secondary structures near physiological (310-315 K) temperatures. Our trajectories indicate that the temperature-dependent burial of hydrophobic patches in the ELP region, coupled to the local water structure dynamics and mediated by intramolecular contacts between aliphatic side chains, correlates with the temperature-dependent structural transitions in known ELP polymers. Because of the link between compaction of ELP segments into ß-rich structures and differential solvation properties of this region, we posit that future variation of ELP sequence and composition can be used to systematically alter the phase transition profiles and, thus, the general functionality of our LG-ELP fusion protein system.

Base-resolution models of transcription-factor binding reveal soft motif syntax.

The arrangement (syntax) of transcription factor (TF) binding motifs is an important part of the cis-regulatory code, yet remains elusive. We introduce a deep learning model, BPNet, that uses DNA sequence to predict base-resolution chromatin immunoprecipitation (ChIP)-nexus binding profiles of pluripotency TFs. We develop interpretation tools to learn predictive motif representations and identify soft syntax rules for cooperative TF binding interactions. Strikingly, Nanog preferentially binds with helical periodicity, and TFs often cooperate in a directional manner, which we validate using clustered regularly interspaced short palindromic repeat (CRISPR)-induced point mutations. Our model represents a powerful general approach to uncover the motifs and syntax of cis-regulatory sequences in genomics data.

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 (DPCTT). 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 DPCTT preferentially samples conformations that are geometrically well-suited as substrates for processive phosphorylation by the cognate kinase GSK3. We suggest that DPCTT 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 DPCTT can contact other parts of DP, suggesting a competitive binding mechanism for the modulation of DP···IF interactions.

Known structure, unknown function: An inquiry-based undergraduate biochemistry laboratory course.

Undergraduate biochemistry laboratory courses often do not provide students with an authentic research experience, particularly when the express purpose of the laboratory is purely instructional. However, an instructional laboratory course that is inquiry- and research-based could simultaneously impart scientific knowledge and foster a student's research expertise and confidence. We have developed a year-long undergraduate biochemistry laboratory curriculum wherein students determine, via experiment and computation, the function of a protein of known three-dimensional structure. The first half of the course is inquiry-based and modular in design; students learn general biochemical techniques while gaining preparation for research experiments in the second semester. Having learned standard biochemical methods in the first semester, students independently pursue their own (original) research projects in the second semester. This new curriculum has yielded an improvement in student performance and confidence as assessed by various metrics. To disseminate teaching resources to students and instructors alike, a freely accessible Biochemistry Laboratory Education resource is available at http://biochemlab.org.