Daniel J. Mandell

Rosetta3: An Object-Oriented Software Suite for the Simulation and Design of Macromolecules

We have recently completed a full re-architecturing of the ROSETTA molecular modeling program, generalizing and expanding its existing functionality. The new architecture enables the rapid prototyping of novel protocols by providing easy-to-use interfaces to powerful tools for molecular modeling. The source code of this rearchitecturing has been released as ROSETTA3 and is freely available for academic use. At the time of its release, it contained 470,000 lines of code. Counting currently unpublished protocols at the time of this writing, the source includes 1,285,000 lines. Its rapid growth is a testament to its ease of use. This chapter describes the requirements for our new architecture, justifies the design decisions, sketches out central classes, and highlights a few of the common tasks that the new software can perform.

Sub-angstrom accuracy in protein loop reconstruction by robotics-inspired conformational sampling

Sub-angstrom accuracy in protein loop reconstruction by robotics-inspired conformational sampling

Biocontainment of genetically modified organisms by synthetic protein design

Genetically modified organisms (GMOs) are increasingly deployed at large scales and in open environments. Genetic biocontainment strategies are needed to prevent unintended proliferation of GMOs in natural ecosystems. Existing biocontainment methods are insufficient because they impose evolutionary pressure on the organism to eject the safeguard by spontaneous mutagenesis or horizontal gene transfer, or because they can be circumvented by environmentally available compounds. Here we computationally redesign essential enzymes in the first organism possessing an altered genetic code (Escherichia coli strain C321.ΔA) to confer metabolic dependence on non-standard amino acids for survival. The resulting GMOs cannot metabolically bypass their biocontainment mechanisms using known environmental compounds, and they exhibit unprecedented resistance to evolutionary escape through mutagenesis and horizontal gene transfer. This work provides a foundation for safer GMOs that are isolated from natural ecosystems by a reliance on synthetic metabolites.

Computer-aided design of functional protein interactions

Predictive methods for the computational design of proteins search for amino acid sequences adopting desired structures that perform specific functions. Typically, design of function is formulated as engineering new and altered binding activities into proteins. Progress in the design of functional protein-protein interactions is directed toward engineering proteins to precisely control biological processes by specifically recognizing desired interaction partners while avoiding competitors. The field is aiming for strategies to harness recent advances in high-resolution computational modeling-particularly those exploiting protein conformational variability-to engineer new functions and incorporate many functional requirements simultaneously.

A Mechanism for Tunable Autoinhibition in the Structure of a Human Ca2+/Calmodulin- Dependent Kinase II Holoenzyme

Summary Calcium/calmodulin-dependent kinase II (CaMKII) forms a highly conserved dodecameric assembly that is sensitive to the frequency of calcium pulse trains. Neither the structure of the dodecameric assembly nor how it regulates CaMKII are known. We present the crystal structure of an autoinhibited full-length human CaMKII holoenzyme, revealing anxa0unexpected compact arrangement of kinase domains docked against a central hub, with the calmodulin-binding sites completely inaccessible. We show that this compact docking is important for the autoinhibition of the kinase domains and for setting the calcium response of the holoenzyme. Comparison of CaMKII isoforms, which differ in the length of the linker between the kinase domain and the hub, demonstrates that these interactions can be strengthened or weakened by changes in linker length. This equilibrium between autoinhibited states provides a simple mechanism for tuning the calcium response without changes in either the hub or the kinase domains. PaperFlick

Backbone flexibility in computational protein design

The field of computational protein design has produced striking successes, including the engineering of novel enzymes. Many of these achievements employed methodologies that sample amino acid side-chains on a fixed backbone, while methods that explicitly model backbone flexibility have so far largely focused on the design of new structures rather than functions. Recent methodological improvements in conformational sampling techniques, some borrowed from the field of robotics to model mechanically accessible conformations, now provide exciting opportunities to explore amino acid sequences and backbone structures simultaneously. Incorporating functional constraints into flexible backbone design should help to achieve challenging engineering goals that exploit the role of conformational variability in controlling biological processes, while more generally advancing biophysical understanding of the relationship between variations in protein sequence, structure, dynamics, and function.

A general strategy to construct small molecule biosensors in eukaryotes.

Biosensors for small molecules can be used in applications that range from metabolic engineering to orthogonal control of transcription. Here, we produce biosensors based on a ligand-binding domain (LBD) by using a method that, in principle, can be applied to any target molecule. The LBD is fused to either a fluorescent protein or a transcriptional activator and is destabilized by mutation such that the fusion accumulates only in cells containing the target ligand. We illustrate the power of this method by developing biosensors for digoxin and progesterone. Addition of ligand to yeast, mammalian, or plant cells expressing a biosensor activates transcription with a dynamic range of up to ~100-fold. We use the biosensors to improve the biotransformation of pregnenolone to progesterone in yeast and to regulate CRISPR activity in mammalian cells. This work provides a general methodology to develop biosensors for a broad range of molecules in eukaryotes. DOI: http://dx.doi.org/10.7554/eLife.10606.001

Assessment of flexible backbone protein design methods for sequence library prediction in the therapeutic antibody Herceptin–HER2 interface

Computational protein design methods can complement experimental screening and selection techniques by predicting libraries of low‐energy sequences compatible with a desired structure and function. Incorporating backbone flexibility in computational design allows conformational adjustments that should broaden the range of predicted low‐energy sequences. Here, we evaluate computational predictions of sequence libraries from different protocols for modeling backbone flexibility using the complex between the therapeutic antibody Herceptin and its target human epidermal growth factor receptor 2 (HER2) as a model system. Within the program RosettaDesign, three methods are compared: The first two use ensembles of structures generated by Monte Carlo protocols for near‐native conformational sampling: kinematic closure (KIC) and backrub, and the third method uses snapshots from molecular dynamics (MD) simulations. KIC or backrub methods were better able to identify the amino acid residues experimentally observed by phage display in the Herceptin–HER2 interface than MD snapshots, which generated much larger conformational and sequence diversity. KIC and backrub, as well as fixed backbone simulations, captured the key mutation Asp98Trp in Herceptin, which leads to a further threefold affinity improvement of the already subnanomolar parental Herceptin‐HER2 interface. Modeling subtle backbone conformational changes may assist in the design of sequence libraries for improving the affinity of antibody–antigen interfaces and could be suitable for other protein complexes for which structural information is available.

Corrigendum: Biocontainment of genetically modified organisms by synthetic protein design.

This corrects the article DOI: 10.1038/nature14121