Maintaining solvent accessible surface area under rotamer substitution for protein design

Fusion crystallization reveals the behavior of both the 1TEL crystallization chaperone and the TNK1 UBA domain

Human thirty-eight-negative kinase-1 (TNK1) is implicated in cancer progression. The TNK1 ubiquitin-associated (UBA) domain binds polyubiquitin and plays a regulatory role in TNK1 activity and stability. No experimentally determined molecular structure of this unusual UBA domain is available. We fused the UBA domain to the 1TEL variant of the translocation ETS leukemia protein sterile alpha motif (TELSAM) crystallization chaperone and obtained crystals diffracting as far as 1.53 Å. GG and GSGG linkers allowed the UBA to reproducibly find a productive binding mode against its host 1TEL polymer and crystallize at protein concentrations as low as 0.2 mg/mL. Our studies support a mechanism of 1TEL fusion crystallization and show that 1TEL fusion crystals require fewer crystal contacts than traditional protein crystals. Modeling and experimental validation suggest the UBA domain may be selective for both the length and linkages of polyubiquitin chains.

Fusion crystallization reveals the behavior of both the 1TEL crystallization chaperone and the TNK1 UBA domain

Human thirty-eight-negative kinase-1 (TNK1) is implicated in cancer progression. The TNK1-UBA domain binds polyubiquitin and plays a regulatory role in TNK1 activity and stability. Sequence analysis suggests an unusual architecture for the TNK1 UBA domain, but an experimentally-validated molecular structure is undetermined. To gain insight into TNK1 regulation, we fused the UBA domain to the 1TEL crystallization chaperone and obtained crystals diffracting as far as 1.53 Å. A 1TEL search model enabled solution of the X-ray phases. GG and GSGG linkers allowed the UBA to reproducibly find a productive binding mode against its host 1TEL polymer and to crystallize at protein concentrations as low as 0.1 mg/mL. Our studies support a mechanism of TELSAM fusion crystallization and show that TELSAM fusion crystals require fewer crystal contacts than traditional protein crystals. Modeling and experimental validation suggest the UBA domain may be selective for both the length and linkages of polyubiquitin chains.

An artificial neural network model to predict structure-based protein-protein free energy of binding from Rosetta-calculated properties

The prediction of the free energy (ΔG) of binding for protein-protein complexes is of general scientific interest as it has a variety of applications in the fields of molecular and chemical biology, materials science, and biotechnology. Despite its centrality in understanding protein association phenomena and protein engineering, the ΔG of binding is a daunting quantity to obtain theoretically. In this work, we devise a novel Artificial Neural Network (ANN) model to predict the ΔG of binding for a given three-dimensional structure of a protein-protein complex with Rosetta-calculated properties. Our model was tested using two data sets, and it presented a root-mean-square error ranging from 1.67 kcal mol^-1 to 2.45 kcal mol^-1, showing a better performance compared to the available state-of-the-art tools. Validation of the model for a variety of protein-protein complexes is showcased.

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.

OPUS-Rota2: An Improved Fast and Accurate Side-Chain Modeling Method

Side-chain modeling plays a critical role in protein structure prediction. However, in many current methods, balancing the speed and accuracy is still challenging. In this paper, on the basis of our previous work OPUS-Rota (Protein Sci. 2008, 17, 1576-1585), we introduce a new side-chain modeling method, OPUS-Rota2, which is tested on both a 65-protein test set (DB65) in the OPUS-Rota paper and a 379-protein test set (DB379) in the SCWRL4 paper. If the main chain is native, OPUS-Rota2 is more accurate than OPUS-Rota, SCWRL4, and OSCAR-star but slightly less accurate than OSCAR-o. Also, if the main chain is non-native, OPUS-Rota2 is more accurate than any other method. Moreover, OPUS-Rota2 is significantly faster than any other method, in particular, 2 orders of magnitude faster than OSCAR-o. Thus, the combination of higher accuracy and speed of OPUS-Rota2 in modeling side chains on both the native and non-native main chains makes OPUS-Rota2 a very useful tool in protein structure modeling.

Computational protein design with explicit consideration of surface hydrophobic patches

De novo protein design requires the identification of amino-acid sequences that favor the target-folded conformation and are soluble in water. One strategy for promoting solubility is to disallow hydrophobic residues on the protein surface during design. However, naturally occurring proteins often have hydrophobic amino acids on their surface that contribute to protein stability via the partial burial of hydrophobic surface area or play a key role in the formation of protein-protein interactions. A less restrictive approach for surface design that is used by the modeling program Rosetta is to parameterize the energy function so that the number of hydrophobic amino acids designed on the protein surface is similar to what is observed in naturally occurring monomeric proteins. Previous studies with Rosetta have shown that this limits surface hydrophobics to the naturally occurring frequency (∼28%), but that it does not prevent the formation of hydrophobic patches that are considerably larger than those observed in naturally occurring proteins. Here, we describe a new score term that explicitly detects and penalizes the formation of hydrophobic patches during computational protein design. With the new term, we are able to design protein surfaces that include hydrophobic amino acids at naturally occurring frequencies, but do not have large hydrophobic patches. By adjusting the strength of the new score term, the emphasis of surface redesigns can be switched between maintaining solubility and maximizing folding free energy.

A proposal for the revision of molecular boundary typology

Molecular shape is essential in understanding molecular function, and understanding molecular shape requires definition of molecular boundaries. In this paper, we review the conceptual evolution of three molecular boundary types: the van der Waals surface, the Connolly surface, and the Lee-Richards (accessible) surface. Then, we point out the confusion among the names of these surfaces existing in the literature. Since it is desirable to have a well-defined terminology in a discipline, we propose the standard names of the three molecular boundary types and their corresponding volumes in order to maximize consistency among researchers, respect the first individual who defined or computed a surface type, and promote collaboration between biologists and geometers.

Computational design of a PAK1 binding protein

We describe a computational protocol, called DDMI, for redesigning scaffold proteins to bind to a specified region on a target protein. The DDMI protocol is implemented within the Rosetta molecular modeling program and uses rigid-body docking, sequence design, and gradient-based minimization of backbone and side-chain torsion angles to design low-energy interfaces between the scaffold and target protein. Iterative rounds of sequence design and conformational optimization were needed to produce models that have calculated binding energies that are similar to binding energies calculated for native complexes. We also show that additional conformation sampling with molecular dynamics can be iterated with sequence design to further lower the computed energy of the designed complexes. To experimentally test the DDMI protocol, we redesigned the human hyperplastic discs protein to bind to the kinase domain of p21-activated kinase 1 (PAK1). Six designs were experimentally characterized. Two of the designs aggregated and were not characterized further. Of the remaining four designs, three bound to the PAK1 with affinities tighter than 350 muM. The tightest binding design, named Spider Roll, bound with an affinity of 100 muM. NMR-based structure prediction of Spider Roll based on backbone and (13)C(beta) chemical shifts using the program CS-ROSETTA indicated that the architecture of human hyperplastic discs protein is preserved. Mutagenesis studies confirmed that Spider Roll binds the target patch on PAK1. Additionally, Spider Roll binds to full-length PAK1 in its activated state but does not bind PAK1 when it forms an auto-inhibited conformation that blocks the Spider Roll target site. Subsequent NMR characterization of the binding of Spider Roll to PAK1 revealed a comparably small binding 'on-rate' constant (<<10(5) M(-1) s(-1)). The ability to rationally design the site of novel protein-protein interactions is an important step towards creating new proteins that are useful as therapeutics or molecular probes.

Metal templated design of protein interfaces

Metal coordination is a key structural and functional component of a large fraction of proteins. Given this dual role we considered the possibility that metal coordination may have played a templating role in the early evolution of protein folds and complexes. We describe here a rational design approach, Metal Templated Interface Redesign (MeTIR), that mimics the time course of a hypothetical evolutionary pathway for the formation of stable protein assemblies through an initial metal coordination event. Using a folded monomeric protein, cytochrome cb(562), as a building block we show that its non-self-associating surface can be made self-associating through a minimal number of mutations that enable Zn coordination. The protein interfaces in the resulting Zn-directed, D(2)-symmetrical tetramer are subsequently redesigned, yielding unique protein architectures that self-assemble in the presence or absence of metals. Aside from its evolutionary implications, MeTIR provides a route to engineer de novo protein interfaces and metal coordination environments that can be tuned through the extensive noncovalent bonding interactions in these interfaces.

Computer-based redesign of a beta sandwich protein suggests that extensive negative design is not required for de novo beta sheet design

The de novo design of globular beta sheet proteins remains largely an unsolved problem. It is unclear whether most designs are failing because the designed sequences do not have favorable energies in the target conformations or whether more emphasis should be placed on negative design, that is, explicitly identifying sequences that have poor energies when adopting undesired conformations. We tested whether we could redesign the sequence of a naturally occurring beta sheet protein, tenascin, with a design algorithm that does not include explicit negative design. Denaturation experiments indicate that the designs are significantly more stable than the wild-type protein and the crystal structure of one design closely matches the design model. These results suggest that extensive negative design is not required to create well-folded beta sandwich proteins. However, it is important to note that negative design elements may be encoded in the conformation of the protein backbone which was preserved from the wild-type protein.

OPUS-Rota: a fast and accurate method for side-chain modeling

In this paper, we introduce a fast and accurate side-chain modeling method, named OPUS-Rota. In a benchmark comparison with the methods SCWRL, NCN, LGA, SPRUCE, Rosetta, and SCAP, OPUS-Rota is shown to be much faster than all the methods except SCWRL, which is comparably fast. In terms of overall chi (1) and chi (1+2) accuracies, however, OPUS-Rota is 5.4 and 8.8 percentage points better, respectively, than SCWRL. Compared with NCN, which has the best accuracy in the literature, OPUS-Rota is 1.6 percentage points better for overall chi (1+2) but 0.3 percentage points weaker for overall chi (1). Hence, our algorithm is much more accurate than SCWRL with similar execution speed, and it has accuracy comparable to or better than the most accurate methods in the literature, but with a runtime that is one or two orders of magnitude shorter. In addition, OPUS-Rota consistently outperforms SCWRL on the Wallner and Elofsson homology-modeling benchmark set when the sequence identity is greater than 40%. We hope that OPUS-Rota will contribute to high-accuracy structure refinement, and the computer program is freely available for academic users.