As molecular dynamics (MD) simulations continue to evolve into powerful computational tools for studying complex biomolecular systems, the necessity of flexible and easy-to-use software tools for the analysis of these simulations is growing. We have developed MDTraj, a modern, lightweight, and fast software package for analyzing MD simulations. MDTraj reads and writes trajectory data in a wide variety of commonly used formats. It provides a large number of trajectory analysis capabilities including minimal root-mean-square-deviation calculations, secondary structure assignment, and the extraction of common order parameters. The package has a strong focus on interoperability with the wider scientific Python ecosystem, bridging the gap between MD data and the rapidly growing collection of industry-standard statistical analysis and visualization tools in Python. MDTraj is a powerful and user-friendly software package that simplifies the analysis of MD data and connects these datasets with the modern interactive data science software ecosystem in Python.

Markov State Models (MSMs) provide an automated framework to investigate the dynamical properties of high-dimensional molecular simulations. These models can provide a human-comprehensible picture of the underlying process, and have been successfully used to study protein folding, protein aggregation, protein ligand binding, and other biophysical systems. The MSM requires the construction of a discrete state-space such that two points are in the same state if they can interconvert rapidly. In the following, we suggest an improved method, which utilizes second order Independent Components Analysis (also known as time-structure based Independent Components Analysis, or tICA), to construct the state-space. We apply this method to simulations of NTL9 (provided by Lindorff-Larsen et al. Science 2011), and show that the MSM is an improvement over previously built models using conventional distance metrics. Additionally, the resulting model provides insight into the role of non-native contacts by revealing many slow timescales associated with compact, non-native states.

Emerging infectious diseases threaten human and wildlife populations. Altered ecological interactions between mutualistic microbes and hosts can result in disease, but an understanding of interactions between host, microbes and disease-causing organisms may lead to management strategies to affect disease outcomes. Many amphibian species in relatively pristine habitats are experiencing dramatic population declines and extinctions due to the skin disease chytridiomycosis, which is caused by the chytrid fungus Batrachochytrium dendrobatidis. Using a randomized, replicated experiment, we show that adding an antifungal bacterial species, Janthinobacterium lividum, found on several species of amphibians to the skins of the frog Rana muscosa prevented morbidity and mortality caused by the pathogen. The bacterial species produces the anti-chytrid metabolite violacein, which was found in much higher concentrations on frog skins in the treatments where J. lividum was added. Our results show that cutaneous microbes are a part of amphibians' innate immune system, the microbial community structure on frog skins is a determinant of disease outcome and altering microbial interactions on frog skins can prevent a lethal disease outcome. A bioaugmentation strategy may be an effective management tool to control chytridiomycosis in amphibian survival assurance colonies and in nature.

Summary: MDTraj is a modern, lightweight and efficient software package for analyzing molecular dynamics simulations. MDTraj reads trajectory data from a wide variety of commonly used formats. It provides a large number of trajectory analysis capabilities including RMSD, DSSP secondary structure assignment and the extraction of common order parameters. The package has a strong focus on interoperability with the wider scientific Python ecosystem, bridging the gap between molecular dynamics data and the rapidly-growing collection of industry-standard statistical analysis and visualization tools in Python.Availability: Package downloads, detailed examples and full documentation are available at

MSMBuilder is a software package for building statistical models of high-dimensional time-series data. It is designed with a particular focus on the analysis of atomistic simulations of biomolecular dynamics such as protein folding and conformational change. MSMBuilder is named for its ability to construct Markov state models (MSMs), a class of models that has gained favor among computational biophysicists. In addition to both well-established and newer MSM methods, the package includes complementary algorithms for understanding time-series data such as hidden Markov models and time-structure based independent component analysis. MSMBuilder boasts an easy to use command-line interface, as well as clear and consistent abstractions through its Python application programming interface. MSMBuilder was developed with careful consideration for compatibility with the broader machine learning community by following the design of scikit-learn. The package is used primarily by practitioners of molecular dynamics, but is just as applicable to other computational or experimental time-series measurements.

Disease has spurred declines in global amphibian populations. In particular, the fungal pathogen Batrachochytrium dendrobatidis has decimated amphibian diversity in some areas unaffected by habitat loss. However, there is little evidence to explain how some amphibian species persist despite infection or even clear the pathogen beyond detection. One hypothesis is that certain bacterial symbionts on the skin of amphibians inhibit the growth of the pathogen. An antifungal strain of Janthinobacterium lividum, isolated from the skin of the red-backed salamander Plethodon cinereus, produces antifungal metabolites at concentrations lethal to B. dendrobatidis. Antifungal metabolites were identified by using reversed phase high performance liquid chromatography, high resolution mass spectrometry, nuclear magnetic resonance, and UV-Vis spectroscopy and tested for efficacy of inhibiting the pathogen. Two metabolites, indole-3-carboxaldehyde and violacein, inhibited the pathogen's growth at relatively low concentrations (68.9 and 1.82 microM, respectively). Analysis of fresh salamander skin confirmed the presence of J. lividum and its metabolites on the skin of host salamanders in concentrations high enough to hinder or kill the pathogen (51 and 207 microM, respectively). These results support the hypothesis that cutaneous, mutualistic bacteria play a role in amphibian resistance to fungal disease. Exploitation of this biological process may provide long-term resistance to B. dendrobatidis for vulnerable amphibians and serve as a model for managing future emerging diseases in wildlife populations.

The allure of a molecular dynamics simulation is that, given a sufficiently accurate force field, it can provide an atomic-level view of many interesting phenomena in biology. However, the result of a simulation is a large, high-dimensional time series that is difficult to interpret. Recent work has introduced the time-structure based Independent Components Analysis (tICA) method for analyzing MD, which attempts to find the slowest decorrelating linear functions of the molecular coordinates. This method has been used in conjunction with Markov State Models (MSMs) to provide estimates of the characteristic eigenprocesses contained in a simulation (e.g., protein folding, ligand binding). Here, we extend the tICA method using the kernel trick to arrive at nonlinear solutions. This is a substantial improvement as it allows for kernel-tICA (ktICA) to provide estimates of the characteristic eigenprocesses directly without building an MSM.

The disease chytridiomycosis, which is caused by the chytrid fungus Batrachochytrium dendrobatidis, is associated with recent declines in amphibian populations. Susceptibility to this disease varies among amphibian populations and species, and resistance appears to be attributable in part to the presence of antifungal microbial species associated with the skin of amphibians. The betaproteobacterium Janthinobacterium lividum has been isolated from the skins of several amphibian species and produces the antifungal metabolite violacein, which inhibits B. dendrobatidis. In this study, we added J. lividum to red-backed salamanders (Plethodon cinereus) to obtain an increased range of violacein concentrations on the skin. Adding J. lividum to the skin of the salamander increased the concentration of violacein on the skin, which was strongly associated with survival after experimental exposure to B. dendrobatidis. As expected from previous work, some individuals that did not receive J. lividum and were exposed to B. dendrobatidis survived. These individuals had concentrations of bacterially produced violacein on their skins that were predicted to kill B. dendrobatidis. Our study suggests that a threshold violacein concentration of about 18 M on a salamander's skin prevents mortality and morbidity caused by B. dendrobatidis. In addition, we show that over one-half of individuals in nature support antifungal bacteria that produce violacein, which suggests that there is a mutualism between violaceinproducing bacteria and P. cinereus and that adding J. lividum is effective for protecting individuals that lack violacein-producing skin bacteria.The amphibian fungal pathogen Batrachochytrium dendrobatidis causes a lethal skin disease that has caused substantial declines in amphibian populations (18). However, some species, such as the bullfrog (Rana catesbeiana) and the tiger salamander (Ambystoma tigrinum), are relatively asymptomatic when they are infected with this pathogen (4, 5). Variation in survival among species has been attributed to differences in innate immune factors, such as antimicrobial peptides (20) and skin-associated microbial species (8-11), as well as behavior (16). The presence of antifungal microbes is of particular interest because it suggests that these organisms are mutualistic associates of amphibian species. In addition, augmentation of the cutaneous microbial community by adding species of bacteria that inhibit B. dendrobatidis has the potential to provide resistance to chytridiomycosis (9).We have identified a number of bacteria associated with the skin of amphibians that inhibit B. dendrobatidis in vitro via secretion of antifungal metabolites (2,3,10,11). The bacterial species used in this study, Janthinobacterium lividum, produces the anti-B. dendrobatidis metabolites violacein and indole-3-carboxaldehyde (MIC, 1.82 M and 69 M, respectively) (3). We have shown that violacein inhibits B. dendrobatidis in laboratory assays (3) and is strongly correlated with survival in vivo of the frog species Ra...