Macromolecular modeling and design in Rosetta: recent methods and frameworks

The Rosetta software for macromolecular modeling, docking and design is extensively used in laboratories worldwide. During two decades of development by a community of laboratories at more than 60 institutions, Rosetta has been continuously refactored and extended. Its advantages are its performance and interoperability between broad modeling capabilities. Here we review tools developed in the last 5 years, including over 80 methods. We discuss improvements to the score function, user interfaces and usability. Rosetta is available at http://www.rosettacommons.org.

Integration of the Rosetta suite with the python software stack via reproducible packaging and core programming interfaces for distributed simulation

The Rosetta software suite for macromolecular modeling is a powerful computational toolbox for protein design, structure prediction, and protein structure analysis. The development of novel Rosetta-based scientific tools requires two orthogonal skill sets: deep domain-specific expertise in protein biochemistry and technical expertise in development, deployment, and analysis of molecular simulations. Furthermore, the computational demands of molecular simulation necessitate large scale cluster-based or distributed solutions for nearly all scientifically relevant tasks. To reduce the technical barriers to entry for new development, we integrated Rosetta with modern, widely adopted computational infrastructure. This allows simplified deployment in large-scale cluster and cloud computing environments, and effective reuse of common libraries for simulation execution and data analysis. To achieve this, we integrated Rosetta with the Conda package manager; this simplifies installation into existing computational environments and packaging as docker images for cloud deployment. Then, we developed programming interfaces to integrate Rosetta with the PyData stack for analysis and distributed computing, including the popular tools Jupyter, Pandas, and Dask. We demonstrate the utility of these components by generating a library of a thousand de novo disulfide-rich miniproteins in a hybrid simulation that included cluster-based design and interactive notebook-based analyses. Our new tools enable users, who would otherwise not have access to the necessary computational infrastructure, to perform state-of-the-art molecular simulation and design with Rosetta.

In-vitro susceptibilities of Pseudomonas aeruginosa and Pseudomonas spp. to the new fluoroquinolones clinafloxacin and PD 131628 and nine other antimicrobial agents

The in-vitro activities of two new fluoroquinolones, clinafloxacin (CI-960, PD 127391, AM-1091) and PD 131628 (the active component of the pro-drug CI-990, PD 131112) and nine other antibiotics were tested against 107 clinical isolates of Pseudomonas aeruginosa, 12 isolates of Xanthomonas maltophilia, and 19 isolates of other Pseudomonas spp. Of the 107 P. aeruginosa isolates, 33 were resistant to gentamicin, tobramycin and amikacin, 17 were resistant to only one or two of these aminoglycosides and 24 were aminoglycoside sensitive. Thirty-three were isolates from cystic fibrosis patients. Susceptibility studies were performed using the agar dilution technique and kinetic time kill curves. With the exception of aminoglycoside-sensitive P. aeruginosa isolates where ciprofloxacin had similar activity to clinafloxacin and PD 131628, the two new fluoroquinolones were the most active agents against all isolates tested (MIC90 0.25-2.0 mg/L). Cross-resistance was identified with ciprofloxacin and ofloxacin-resistant strains, but the superior activity of clinafloxacin and PD 131628 resulted in 90% of the isolates having MICs < 2 mg/L. Kinetic kill curves with aminoglycoside-sensitive P. aeruginosa revealed ciprofloxacin to have the most rapid and sustained killing. However, with amino-glycoside-resistant P. aeruginosa isolates, clinafloxacin and PD 131628 were more rapidly bactericidal than ciprofloxacin.

Health Education and the primary care physician: the practitioner's perspective

Considering the attention given to health education and promotion, it is surprising that little research assesses the opinions and behavioral inclinations of physicians. Survey data collected in Florida address this issue. Responses of primary care private practitioners reveal that whereas MDs endorse health promotion and acknowledge a link between positive lifestyle and health, their outlook regarding the potential of community-based health education remains skeptical. A majority blame ineffective health education on public apathy. Nonetheless, a sizeable minority are willing to either begin or increase their involvement in health education programs. Multivariate analyses suggest that active or receptive MDs view the public's lifestyle knowledge as inadequate and select the MD as the health professional most suited to assume primary responsibility for health education. Clues for identifying practitioners who might engage in further health education are provided by examining age, specialty, patient load and community size. For example, GPs/FPs might more readily endorse an educational program if it allows for one-to-one physician-patient interaction; emphasizing this instructional mode appears less important in securing the cooperation of their more specialized primary care counterparts. Further, MDs with the larger caseloads are more likely to view health education as the physician's responsibility.