Donor-Derived West Nile Virus Infection in Solid Organ Transplant Recipients

We describe four solid-organ transplant recipients with donor-derived West Nile virus (WNV) infection (encephalitis 3, asymptomatic 1) from a common donor residing in a region of increased WNV activity. All four transplant recipients had molecular evidence of WNV infection in their serum and/or cerebrospinal fluid (CSF) by reverse transcription polymerase chain reaction (RT-PCR) testing. Serum from the organ donor was positive for WNV IgM but negative for WNV RNA, whereas his lymph node and spleen tissues tested positive for WNV by RT-PCR. Combination therapy included intravenous immunoglobulin (4 cases), interferon (3 cases), fresh frozen plasma with WNV IgG (2 cases), and ribavirin (1 case). Two of the four transplant recipients survived.Review of the 20 published cases of organ-derived WNV infection found that this infection is associated with a high incidence of neuroinvasive disease (70%) and severe morbidity and mortality (30%). Median time to onset of symptomatic WNV infection was 13 days after transplantation (range 5-37 days). Initial unexplained fever unresponsive to antibiotic therapy followed by rapid onset of neurologic deficits was the most common clinical presentation. Confirmation of infection was made by testing serum and CSF for both WNV RNA by RT-PCR and WNV IgM by serological assays. Treatment usually included supportive care, reduction of immunosuppression, and frequent intravenous immunoglobulin. The often negative results for WNV by current RT-PCR and serological assays and the absence of clinical signs of acute infection in donors contribute to the sporadic occurrence of donor-derived WNV infection. Potential organ donors should be assessed for unexplained fever and neurological symptoms, particularly if they reside in areas of increased WNV activity

Anchor extension: a structure-guided approach to design cyclic peptides targeting enzyme active sites

Cyclic peptides are of particular interest due to their pharmacological properties, but their design for binding to a target protein is challenging. Here, the authors present a computational “anchor extension” methodology for de novo design of cyclic peptides that bind to the target protein with high affinity, and validate the approach by developing cyclic peptides that inhibit histone deacetylases 2 and 6

The Rosetta All-Atom Energy Function for Macromolecular Modeling and Design

Over the past decade, the Rosetta biomolecular modeling suite has informed diverse biological questions and engineering challenges ranging from interpretation of low-resolution structural data to design of nanomaterials, protein therapeutics, and vaccines. Central to Rosetta’s success is the energy function: a model parametrized from small-molecule and X-ray crystal structure data used to approximate the energy associated with each biomolecule conformation. This paper describes the mathematical models and physical concepts that underlie the latest Rosetta energy function, called the Rosetta Energy Function 2015 (REF15). Applying these concepts, we explain how to use Rosetta energies to identify and analyze the features of biomolecular models. Finally, we discuss the latest advances in the energy function that extend its capabilities from soluble proteins to also include membrane proteins, peptides containing noncanonical amino acids, small molecules, carbohydrates, nucleic acids, and other macromolecules

Accurate de novo design of hyperstable constrained peptides

Naturally occurring, pharmacologically active peptides constrained with covalent crosslinks generally have shapes that have evolved to fit precisely into binding pockets on their targets. Such peptides can have excellent pharmaceutical properties, combining the stability and tissue penetration of small-molecule drugs with the specificity of much larger protein therapeutics. The ability to design constrained peptides with precisely specified tertiary structures would enable the design of shape-complementary inhibitors of arbitrary targets. Here we describe the development of computational methods for accurate de novo design of conformationally restricted peptides, and the use of these methods to design 18-47 residue, disulfide-crosslinked peptides, a subset of which are heterochiral and/or N-C backbone-cyclized. Both genetically encodable and non-canonical peptides are exceptionally stable to thermal and chemical denaturation, and 12 experimentally determined X-ray and NMR structures are nearly identical to the computational design models. The computational design methods and stable scaffolds presented here provide the basis for development of a new generation of peptide-based drugs

The Rosetta All-Atom Energy Function for Macromolecular Modeling and Design

Over the past decade, the Rosetta biomolecular modeling suite has informed diverse biological questions and engineering challenges ranging from interpretation of low-resolution structural data to design of nanomaterials, protein therapeutics, and vaccines. Central to Rosetta’s success is the energy function: a model parametrized from small-molecule and X-ray crystal structure data used to approximate the energy associated with each biomolecule conformation. This paper describes the mathematical models and physical concepts that underlie the latest Rosetta energy function, called the Rosetta Energy Function 2015 (REF15). Applying these concepts, we explain how to use Rosetta energies to identify and analyze the features of biomolecular models. Finally, we discuss the latest advances in the energy function that extend its capabilities from soluble proteins to also include membrane proteins, peptides containing noncanonical amino acids, small molecules, carbohydrates, nucleic acids, and other macromolecules

Ensuring scientific reproducibility in bio-macromolecular modeling via extensive, automated benchmarks

Each year vast international resources are wasted on irreproducible research. The scientific community has been slow to adopt standard software engineering practices, despite the increases in high-dimensional data, complexities of workflows, and computational environments. Here we show how scientific software applications can be created in a reproducible manner when simple design goals for reproducibility are met. We describe the implementation of a test server framework and 40 scientific benchmarks, covering numerous applications in Rosetta bio-macromolecular modeling. High performance computing cluster integration allows these benchmarks to run continuously and automatically. Detailed protocol captures are useful for developers and users of Rosetta and other macromolecular modeling tools. The framework and design concepts presented here are valuable for developers and users of any type of scientific software and for the scientific community to create reproducible methods. Specific examples highlight the utility of this framework, and the comprehensive documentation illustrates the ease of adding new tests in a matter of hours