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.

Releasing a preprint is associated with more attention and citations for the peer-reviewed article.

Preprints in biology are becoming more popular, but only a small fraction of the articles published in peer-reviewed journals have previously been released as preprints. To examine whether releasing a preprint on bioRxiv was associated with the attention and citations received by the corresponding peer-reviewed article, we assembled a dataset of 74,239 articles, 5,405 of which had a preprint, published in 39 journals. Using log-linear regression and random-effects meta-analysis, we found that articles with a preprint had, on average, a 49% higher Altmetric Attention Score and 36% more citations than articles without a preprint. These associations were independent of several other article- and author-level variables (such as scientific subfield and number of authors), and were unrelated to journal-level variables such as access model and Impact Factor. This observational study can help researchers and publishers make informed decisions about how to incorporate preprints into their work.

Cox regression increases power to detect genotype-phenotype associations in genomic studies using the electronic health record.

BACKGROUND: The growth of DNA biobanks linked to data from electronic health records (EHRs) has enabled the discovery of numerous associations between genomic variants and clinical phenotypes. Nonetheless, although clinical data are generally longitudinal, standard approaches for detecting genotype-phenotype associations in such linked data, notably logistic regression, do not naturally account for variation in the period of follow-up or the time at which an event occurs. Here we explored the advantages of quantifying associations using Cox proportional hazards regression, which can account for the age at which a patient first visited the healthcare system (left truncation) and the age at which a patient either last visited the healthcare system or acquired a particular phenotype (right censoring). RESULTS: In comprehensive simulations, we found that, compared to logistic regression, Cox regression had greater power at equivalent Type I error. We then scanned for genotype-phenotype associations using logistic regression and Cox regression on 50 phenotypes derived from the EHRs of 49,792 genotyped individuals. Consistent with the findings from our simulations, Cox regression had approximately 10% greater relative sensitivity for detecting known associations from the NHGRI-EBI GWAS Catalog. In terms of effect sizes, the hazard ratios estimated by Cox regression were strongly correlated with the odds ratios estimated by logistic regression. CONCLUSIONS: As longitudinal health-related data continue to grow, Cox regression may improve our ability to identify the genetic basis for a wide range of human phenotypes.

Simphony: simulating large-scale, rhythmic data.

Simulated data are invaluable for assessing a computational method's ability to distinguish signal from noise. Although many biological systems show rhythmicity, there is no general-purpose tool to simulate large-scale, rhythmic data. Here we present Simphony, an R package for simulating data from experiments in which the abundances of rhythmic and non-rhythmic features (e.g., genes) are measured at multiple time points in multiple conditions. Simphony has parameters for specifying experimental design and each feature's rhythmic properties (e.g., amplitude and phase). In addition, Simphony can sample measurements from Gaussian and negative binomial distributions, the latter of which approximates read counts from RNA-seq data. We show an example of using Simphony to evaluate the accuracy of rhythm detection. Our results suggest that Simphony will aid experimental design and computational method development. Simphony is thoroughly documented and freely available at https://github.com/hugheylab/simphony.

Commonly used fluoroquinolones cross-react with urine drug screens for opiates, buprenorphine, and amphetamines.

OBJECTIVES: Fluoroquinolone antibiotics are commonly used in the treatment of infections and have previously been confirmed to cross-react with previous generations of opiates immunoassays. In this work we evaluated the cross-reactivity of the three fluoroquinolones in use at our institution with a panel of 10 urine drug screens. DESIGN AND METHODS: Drug preparations of levofloxacin, ciprofloxacin, and moxifloxacin that were designed for intravenous delivery were added to drug-free urine at varying concentrations. Spiked urine samples were screened for illicit and therapeutic drugs on an Abbott Architect c16000 automated chemistry analyzer. Percent cross-reactivity was calculated. RESULTS: Levofloxacin displayed clinically relevant cross-reactivity with the Abbott MULTIGENT opiates and Thermo CEDIA® buprenorphine immunoassays but did not cross-react with the Abbott MULTIGENT oxycodone or methadone immunoassays. Moxifloxacin displayed clinically relevant cross-reactivity only with the Abbott MULTIGENT amphetamine/methamphetamine assay. Ciprofloxacin did not cross-react with any of the 10 immunoassays. CONCLUSIONS: This study demonstrates that levofloxacin cross-reacts with modern immunoassays for two related opioids (buprenorphine and morphine) and moxifloxacin cross-reacts with the amphetamine/methamphetamine assay. Urine concentrations of these fluoroquinolones that are consistent with therapeutic use produced results above commonly used-cutoffs for positivity. This underscores the necessity of confirmatory testing of presumptively positive urine drug screens.

The STAT5b Linker Domain Mediates the Selectivity of Catechol Bisphosphates for STAT5b over STAT5a.

STAT family proteins are important mediators of cell signaling and represent therapeutic targets for the treatment of human diseases. Most STAT inhibitors target the protein-protein interaction domain, the SH2 domain, but specificity for a single STAT protein is often limited. Recently, we developed catechol bisphosphates as the first inhibitors of STAT5b demonstrated to exhibit a high degree of selectivity over the close homologue STAT5a. Here, we show that the amino acid in position 566 of the linker domain, not the SH2 domain, is the main determinant of specificity. Arg566 in wild-type STAT5b favors tight binding of catechol bisphosphates, while Trp566 in wild-type STAT5a does not. Amino acid 566 also determines the affinity for a tyrosine-phosphorylated peptide derived from the EPO receptor for STAT5a and STAT5b, demonstrating the functional relevance of the STAT5 linker domain for the adjacent SH2 domain. These results provide the first demonstration that a residue in the linker domain can determine the affinity of nonpeptidic small-molecule inhibitors for the SH2 domain of STAT proteins. We propose targeting the interface between the SH2 domain and linker domain as a novel design approach for the development of potent and selective STAT inhibitors. In addition, our data suggest that the linker domain could contribute to the enigmatically divergent biological functions of the two STAT5 proteins.

Predictive Power of Different Types of Experimental Restraints in Small Molecule Docking: A Review.

Incorporating experimental restraints is a powerful method of increasing accuracy in computational protein small molecule docking simulations. Different algorithms integrate distinct forms of biochemical data during the docking and/or scoring stages. These so-called hybrid methods make use of receptor-based information such as nuclear magnetic resonance (NMR) restraints or small molecule-based information such as structure-activity relationships (SARs). A third class of methods directly interrogates contacts between the protein receptor and the small molecule. This work reviews the current state of using such restraints in docking simulations, evaluates their feasibility across broad systems, and identifies potential areas of algorithm development.